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In the best case, authors may provide the sources of -their research as a compressed archive and feel confident their research is -replicable. But this is not exactly -true. [Buckheit & Donoho (1995)](http://statweb.stanford.edu/~wavelab/Wavelab_850/wavelab.pdf) -explained almost 20 years ago that, *an article about computational result is -advertising, not scholarship. The actual scholarship is the full software -environment, code and data that produced the result*. The computational part in -computational sciences implies the use of computers, operating systems, tools, -frameworks, libraries and data. This leads to such a large number of -combinations (taking into account the version for each component) that the -chances to have the exact same configuration as one of your colleagues are -nearly zero. This draws consequences in our respective computational approaches -in order to make sure that computational research can be actually and -faithfully replicated. - -Re**Science** is a peer-reviewed journal that targets computational research -and encourages the explicit replication of already published research, -promoting new and open-source implementations in order to ensure that the -original research is reproducible. To achieve this goal, the whole publishing -chain is radically different from any other traditional scientific -journal. Re**Science** lives on [GitHub](https://github.com/ReScience/) where -each new implementation of a computational study is made available together with comments, explanations -and tests. Each submission takes the form of a pull request that is publicly -reviewed and tested in order to guarantee that any researcher can re-use it. If -you ever replicated computational results from the literature in your research, -Re**Science** is the perfect place to publish your new implementation. - - -## The extent of the problem - -Here is a (very limited) list of publications on the problem of replicability in computational science that motivated the creation of Re**Science**: - -* [Writing Software Specifications](https://www.researchgate.net/profile/Konrad_Hinsen/publication/275412727_Writing_Software_Specifications/links/553e4eb50cf20184050e2062.pdf?origin=publication_detail) - **K. Hinsen**, Computing in Science and Engineering, 2015. - -* [A long journey into reproducible computational neuroscience](http://journal.frontiersin.org/article/10.3389/fncom.2015.00030/full) - M. Topalidou, A. Leblois, T. Boraud and **N.P. Rougier**, Frontiers in Computational Neuroscience, 2015. - -* [Computational science: shifting the focus from tools to models](http://f1000research.com/articles/3-101/v2) - **K. Hinsen**, F1000Research, 2014. - -* [Best Practices for Scientific Computing](http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745) -Greg Wilson , D. A. Aruliah, **C. Titus Brown**, Neil P. Chue Hong, Matt Davis, Richard T. Guy, Steven H. D. Haddock, Kathryn D. Huff, Ian M. Mitchell, Mark D. Plumbley, Ben Waugh, Ethan P. White, Paul Wilson, PLOS Biology, 2014. - -* [Hard road to reproducibility](http://science.sciencemag.org/content/354/6308/142) -**Lorena A. Barba**, Science, Vol. 354, Issue 6308, 2016. -See also [Barba group reproducibility syllabus](https://medium.com/@lorenaabarba/barba-group-reproducibility-syllabus-e3757ee635cf#.h603izuwo) - -* [Learning from the Past: Approaches for Reproducibility in Computational Neuroscience](http://link.springer.com/chapter/10.1007%2F978-1-4614-1424-7_4) -S.M. Crook, **A.P. Davison**, H.E. Plesser, 20 Years of Computational Neuroscience, 2013 -(→ contact [Sharon Crook](http://math.la.asu.edu/~crook) to request a copy). - -* [Four aspects to make science open “by design” and not as an after-thought](http://www.gigasciencejournal.com/content/4/1/31) - Y.O. Halchenko, M.Hanke, GigaScience, 2015. - - -### See also - -* [Push journal](http://push.cwcon.org) - Research & applied theory in writing with sources -* [IPOL Journal](http://www.ipol.im) - Image Processing On Line -* [PSRI](http://projects.iq.harvard.edu/psreplication) - Political Science Replication Initiative diff --git a/01-read.md b/01-read.md deleted file mode 100644 index d136255..0000000 --- a/01-read.md +++ /dev/null @@ -1,8 +0,0 @@ ---- -layout: read -menutitle: READ -permalink: /read/ ---- - - -# Current issue diff --git a/02-write.md b/02-write.md deleted file mode 100644 index 9da5d30..0000000 --- a/02-write.md +++ /dev/null @@ -1,165 +0,0 @@ ---- -layout: page -menutitle: WRITE -permalink: /write/ ---- - -# Overview of the submission process - -The Re**Science** editorial board unites scientists who are committed to the -open source community. They are experienced developers who are -familiar with the GitHub ecosystem. Each editorial board member is specialised -in a specific domain of science and is proficient in several programming -languages and/or environments. Our aim is to provide all authors with an -efficient, constructive and public editorial process. - -Submitted entries are first considered by a member of the editorial board, who -may decide to reject the submission (mainly because it has already been -replicated and is publicly available), or assign it to two reviewers for -further review and tests. The reviewers evaluate the code and the accompanying -material in continuous interaction with the authors through the PR discussion -section. If both reviewers managed to run the code and obtain the same results -as the ones advertised in the accompanying material, the submission is -accepted. If any of the two reviewers cannot replicate the results before the -deadline, the submission is rejected and authors are encouraged to resubmit an -improved version later. - -## Criteria for Publication - -To be considered for publication in Re**Science**, any given submission must -satisfy the following criteria: - -* Replicability -* Rigorous methodology -* Original source code -* Substantial evidence for replication of the original results - -Furthermore, you cannot submit the replication of your own research, nor the -research of your close collaborators. We believe such restrictions will favor -the cross-fertilization of research and the spread of knowledge. - -ReScience accepts negative results as well, meaning here a failure to -replicate the original results. The authors of the failed replication are -expected to document their claim of failure. An attempt to have contacted the -authors of the original article is also asked to the authors of the -replication. - - -## Open Access - -Re**Science** applies the Creative Commons Attribution (CC BY) license to all -works we publish. Under the CC BY license, authors retain ownership of the -copyright for their article, but authors allow anyone to download, reuse, -reprint, modify, distribute, and/or copy articles in Re**Science** journal, so -long as the original authors and source are cited. No permission is required -from the authors or the publishers. - - - -## How to submit ? - -* Create a [GitHub](https://github.com) account -* [Fork](https://github.com/ReScience/ReScience-submission/fork) the - [ReScience submission](https://github.com/ReScience/ReScience-submission) - repository -* Clone this new repository into your desktop environment - - ``` - $ git clone https://github.com/YOUR-USERNAME/ReScience-submission - ``` -* Create a branch (the branch name should be author names separated with dashes) - - ``` - $ git checkout -b AUTHOR1-AUTHOR2-...-AUTHORN-YEAR - ``` -* Add your code & article and commit your changes: - - ``` - $ git commit -a -m "Some comment" - ``` -* [Push](https://help.github.com/articles/pushing-to-a-remote/) to GitHub - - ``` - $ git push origin AUTHOR1-AUTHOR2-...-AUTHORN-YEAR - ``` -* Issue a - [pull request](https://help.github.com/articles/using-pull-requests/) (PR) - to Re**Science** with title "Review Request" and insert the following text - in the description: - - ``` - **AUTHOR** - - Dear @ReScience/editors, - - I request a review for the replication of the following paper: - - * References of the paper holding results you're replicating - - I believed the original results have been faithfully replicated - as explained in the accompanying [article](link to your pdf). - - Repository lives at (link to your repository/branch) - --- - - **EDITOR** - - * [ ] Editor acknowledgment () - * [ ] Reviewer 1 () - * [ ] Reviewer 2 () - * [ ] Review 1 decision [accept/reject] - * [ ] Review 2 decision [accept/reject] - * [ ] Editor decision [accept/reject] - ``` - -* Assign the PR to an editor from the - [editorial board](https://github.com/ReScience/ReScience/wiki/Editorial-Board) -* Answer questions and requests made in the PR conversation page. - -You can have a look at a [previous submission](https://github.com/ReScience/ReScience-submission/pull/3) - - -## Preparation of the material - -The structure of a submission is: - -~~~ -+ README.md -+ article -| | author(s)-YEAR.md -| | author(s)-YEAR.bib -| | LICENSE.md (CC-BY 4.0) -| | ... -| + ... -+ code -| | README.md - | LICENSE.md (to be chosen) -| | ... -| + ... -+ data -| | README.md -| | LICENSE.md (CC 0) -| | ... -| + ... -+ notebook - | README.md - | LICENSE.md (to be chosen) - | - + ... -~~~ - -* A top `README.md` file that will be displayed when a reader enters your - submission directory (once published) -* An `author(s)-YEAR.md` file that introduces the original paper, explains the - technical details of the replication and gives the evidence for the - replication of the original results. -* A `code` directory that contains the **commented** code for the replication. -* A `data` directory that contains any data necessary to run the code. -* A `notebook` directory that may contain notebooks if relevant. -* Don't forget to choose a license for the code repository. You're free to - choose whatever open license you prefer (see - [the Debian Free Software Guidelines](https://www.debian.org/social_contract#guidelines)) - but you need to choose one. -* In the `code/README.md` and `notebook/README.md` files, include information - on the platform that was used to generate the results according to our - [platform instructions](../platform). diff --git a/03-edit.md b/03-edit.md deleted file mode 100644 index c33ec5c..0000000 --- a/03-edit.md +++ /dev/null @@ -1,213 +0,0 @@ ---- -layout: page -menutitle: EDIT -permalink: /edit/ ---- - - -# The reviewing process - -A submission takes the form of a -[Pull Request](https://help.github.com/articles/using-pull-requests/) which is -a mechanism in GitHub to request the integration of some code into a -repository. We use this mechanism as the primary source for the review because -it allows to precisely comment each source and to exchange with the author. If -you're unfamiliar with GitHub, do not hesitate to ask advices and informations -to the editor in charge of editing the submission. You can have a look at what -a full [submission](https://github.com/ReScience/ReScience-submission/pull/3) -looks like. Reviewers unfamiliar with git should have a look at -http://git-lectures.github.io - -To review a submission, you'll first have to clone the author's repository onto -your desktop environment and each time an author update the manuscript or code -to get reviewer's comment into account, you'll have to update your local copy -using the `git pull` command. - -## Reviewer guidelines - -### Successful replications - -Most articles in Re**Science** report the successful replication of the -results (figures, tables, ...) of previously published research work. -A full replication covers all the results of the original work, whereas -a partial replication covers only a subset of the results. - -The main criteria for acceptance are - - 1. The actual replication of the research. The reviewer must evaluate - the authors' claims about a successful replication, applying the - standards of the field. - - 2. Reproducibility of the replication. The reviewers must be able - to run the proposed implementation on their computer, and obtain - the same results as the authors with the limits of the state of - of the art of the field. - - 3. Clarity of the code and the instructions for running it. - Uncommented or obfuscated code is as bad as no code at all. - - 4. Clarity and completeness of the accompanying article, in which the - authors should clearly state why they think they have replicated - the paper (same figures, same graphics, same behavior, etc.) and - explain any obstacles they have encountered during the replication - work. - -The primary goal of the review is not to decide whether to accept or -reject a submission, but to help the authors improve their work until -it meets the Re**Science** quality standards. Since Re**Science** -targets replication of already published research, there is no need to -judge the relevance or novelty of the work. Every replication that -meets the criteria listed above is welcome in Re**Science**. -Rejection remains of course a possiblity, in the case that the -authors are not able or willing to improve their submission as -deemed necessary by the reviewers. - -When evaluating the criteria for acceptance, reviewers need to apply -the standards of their field of research. There are no absolute -criteria for two results/figures being equal, so both the success and -the reproducibility of the replication must be judged according to -the degree of equality that can be achieved given the state of the -art of the field. The clarity of the code and instructions must also -be judged in the light of the conventions of the field. As a general -goal, any competent researcher in the field should understand the -paper and be able to understand and run the code. The use of -software packages that are mainstream in the field is encouraged, -but not strictly required. The less well-known a software package -is, the more explanation authors should provide concerning its -capabilities and use. - -### Failed replications - -A replication attempt can lead to the finding that the results of the -original paper cannot be reproduced, suggesting a mistake or ommission -in the original work. The failure can concern some or all of the results. -Re**Science** accepts reports on replication failures, but requires a -particularly careful examination by the reviewers. The authors must describe -in detail why they believe that the original work is mistaken, and the -reviewers must be convinced by the reasoning offered by the authors. - -Authors who are confronted with replication failure are strongly encouraged -to contact the authors of the original work and try to explore the causes -of the replication failure in collaboration with them. This is, however, not -a requirement for publication in Re**Science**. - - -# The editing process - -The role of a scientific editor is to manage a submission from start to end, i.e. -from the initial acknowledgment request by the editor-in-chief to the final -[publication](../read) (with DOI). As an editor, your goal is to help authors improve their -submission in order to meet the journal's quality standards and to ensure that anyone -can re-use the published code. Depending on the specific domain, an editor might -request the article to follow best practices of the domain. For example, -in computational neuroscience, it may be desirable for models to be formally -described using the proposal of -[Nordlie et al, 2009](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000456). You -can have a look at what a full -[submission](https://github.com/ReScience/ReScience-submission/pull/3) looks -like. - - -## Editor guidelines - -* When a pull request (PR) has been assigned to you, you have to acknowledge - the PR (as a comment in the PR discussion). Depending on your decision, you - can either **reject** and close the PR (and motivate such decision) or - **accept** it and assign one or two reviewers (depending if you intend to - review the PR yourself or not). You alert the reviewers in the PR - acknowledgment (use the @ alert syntax). If you think you cannot handle the - submission within a reasonable delay, you should re-assign the PR to another editor - after having obtained his or her agreement. - -* You have to edit the initial PR text to add some information: - - ``` - **EDITOR** - - * [ ] Editor acknowledgment - * [ ] Review 1 started - * [ ] Review 2 started - * [ ] Review 1 decision [accept/reject] - * [ ] Review 2 decision [accept/reject] - * [ ] Editor decision [accept/reject] - ``` - - You'll need to ask reviewers to add their GitHub login after `review 1 - started` or `review 2 started`. For example `review 1 started (@rougier)` - -* During the review, reviewers are free to interact with the authors in the PR to ask for - clarification or change in any file that is part of the submission. - -* Don't forget to update PR labels according to the status of submission - -* The main criterion for acceptance is the actual replication of the research - with a clear statement by the authors explaining why they think they have - replicated the paper (same figures, same graphics, same behavior, - etc.). However, keep in mind that the clarity of the code is an important - criterion. Uncommented or obfuscated code is as bad as no code at all. A code - without the accompanying article is also a criterion for rejection since - we're not human compilers (well not all of us at least). - -* Don't forget to check that there is a license in the code repository. Authors can - choose whatever open license they prefer (see - [the Debian Free Software Guidelines](https://www.debian.org/social_contract#guidelines)) - but they need to choose one. - -* If both reviewers agree, the paper can be accepted. - - -# The publication process - -The publication is currently far from automatic and requires a number of steps -that are listed here: - - * Lock the conversation on the original PR - * Ask the author(s) for keywords if they haven't provided them already. - * **[Import](https://import.github.com/)** the authors' repository into the - ReScience archives (https://github.com/ReScience-Archives) using the naming - convention "Author(s)-YEAR" - * Add a new remote (named `rescience`) in your local copy of the repository - that points to the newly imported repository (the one on - [ReScience-Archives](https://github.com/ReScience-Archives)) - * Update article metadata: - - Editor name - - Reviewer 1 name - - Reviewer 2 name - - Submission date - - Publication date - - Article repository - - Code repository - - Notebook repository (if necessary) - - Data repository (if necessary) - - Volume, issue and year - - Article number (after reserving the number in the [dedicated GitHub - issue](https://github.com/ReScience/ReScience/issues/48)). - * If the article name is not `Author(s)-YEAR.md`, rename it - * Rebuild the PDF and check everything is OK - * Merge the rescience branch into master - * Push these changes onto the `rescience` remote repository - * Make a [new release](https://help.github.com/articles/creating-releases/): - - Release version number is 1.0 - - Release name is Author(s)-YEAR-1.0 - - * Download the zip file and rename it to `Author(s)-YEAR-1.0.zip` - * Upload this zip file to [Zenodo](https://zenodo.org/deposit/?c=rescience). - You will have to fill several fields: - - Name of the journal is ReScience - - Under "Communities" add "ReScience journal" - - Under "Contributors" add yourself with role "Editor". - - Don't forget keywords - - * Add the `04-Published` label to the PR - * Announce publication in the PR (and quote the DOI, see - [#3](https://github.com/ReScience/ReScience-submission/pull/3) for example) - * Make a PR to the [Web site repository](https://github.com/ReScience/rescience.github.io) - in order to update the page [rescience.github.io/read](http://rescience.github.io/read/). - This requires creating a new post (directory `_posts`) based on this - [model](https://raw.githubusercontent.com/rougier/rescience.github.io/master/_posts/2015-08-14-Topalidou-Rougier.md) - because the page is composed from the posts of type `article`. - * Make a PR to update [Rescience/Volume X - Issue Y.md](https://github.com/ReScience/ReScience) - * Close the PR without merging - * Inform the editors-in-chief about the new publication - * If you're uncertain at any step of the procedure, ask - the editors-in-chief for advice. diff --git a/04-board.md b/04-board.md deleted file mode 100644 index 1bd2124..0000000 --- a/04-board.md +++ /dev/null @@ -1,573 +0,0 @@ ---- -layout: page -menutitle: BOARD -permalink: /board/ ---- - -# Editorial board - -The editorial board is made of people who are committed to the open source -community and are both experienced developers and strongly familiar with the -GitHub ecosystem. Each editorial board member is specialised in a specific -domain of Science and is proficient in several programming languages and/or -environments. While many of us work primarily in Python, ReScience also -accepts submissions in other open source languages. - - -## Editors-in-Chief - -* [Konrad Hinsen](https://github.com/khinsen) - Molecular Biophysics - Python, C, Racket, Clojure - ORCID: [0000-0003-0330-9428](http://orcid.org/0000-0003-0330-9428) - - [Centre de biophysique moléculaire](http://cbm.cnrs-orleans.fr) - Rue Charles Sadron - CS 80054 - 45071 Orléans Cedex 2, France - **Email**: konrad dot hinsen at cnrs dot fr - - - -* [Nicolas P. Rougier](https://github.com/rougier) - [★](https://github.com/ReScience/ReScience-submission/pull/14)[★](https://github.com/ReScience/ReScience-submission/pull/18)[★](https://github.com/ReScience/ReScience-submission/pull/19)[★](https://github.com/ReScience/ReScience-submission/pull/24)[★](https://github.com/ReScience/ReScience-submission/pull/36)[★](https://github.com/ReScience/ReScience-submission/pull/46)[★](https://github.com/ReScience/ReScience-submission/pull/51) - Computational Neuroscience, Computer Science - Python, C/C++ - ORCID: [0000-0002-6972-589X](http://orcid.org/0000-0002-6972-589X) - - [Inria Bordeaux Sud-Ouest](https://www.inria.fr/centre/bordeaux) - 200 Avenue de la vieille tour - 33405 Talence cedex, France - **Email**: nicolas dot rougier at inria dot fr - - - -## Associate Editors - -* [Tiziano Zito](https://github.com/otizonaizit) - [★](https://github.com/ReScience/ReScience-submission/pull/3)[★](https://github.com/ReScience/ReScience-submission/pull/17)[★](https://github.com/ReScience/ReScience-submission/pull/22)[★](https://github.com/ReScience/ReScience-submission/pull/35)[★](https://github.com/ReScience/ReScience-submission/pull/46) - Computational Neuroscience - Python, C, Fortran - ORCID: [---](http://orcid.org/) - - [Freelance consultant](https://github.com/otizonaizit) - Berlin, Germany - - -* [Pierre de Buyl](https://github.com/pdebuyl) - [★](https://github.com/ReScience/ReScience-submission/pull/25)[★](https://github.com/ReScience/ReScience-submission/pull/35) - Computational Physics - Python, C, Fortran - ORCID: [0000-0002-6640-6463](https://orcid.org/0000-0002-6640-6463) - - [Department of Physics and Astronomy](http://fys.kuleuven.be/english/) - [University of Leuven](http://www.kuleuven.be/english/) — - Leuven, Belgium - - -* [Emmanuelle Gouillart](https://github.com/emmanuelle) - [★](https://github.com/ReScience/ReScience-submission/pull/20) - Physics, Image processing - Python - ORCID: [0000-0002-3869-9967](http://orcid.org/0000-0002-3869-9967) - - [Surface du Verre et Interfaces](http://svi.cnrs.fr/spip/) - [CNRS](http://www.cnrs.fr/) / [Saint-Gobain](http://www.saint-gobain-recherche.fr/) — - Aubervilliers, France - - -* [C. Titus Brown](https://github.com/ctb) - [★](https://github.com/ReScience/ReScience-submission/pull/27)[★](https://github.com/ReScience/ReScience-submission/pull/41) - Bioinformatics - Python - ORCID: [0000-0001-6001-2677](http://orcid.org/0000-0001-6001-2677) - - [Population Health and Reproduction](http://www.vetmed.ucdavis.edu/phr/) - [University of California Davis](https://www.ucdavis.edu) — - Davis, California, USA - - -* [Thomas Arildsen](https://github.com/ThomasA) - [★](https://github.com/ReScience/ReScience-submission/pull/28) - Signal Processing - Python, Matlab - ORCID: [0000-0003-3254-3790](http://orcid.org/0000-0003-3254-3790) - - [Department of Electronic Systems](http://www.es.aau.dk) - [Aalborg Universtet](http://www.aau.dk) — - Aalborg, Danemark - - -* [Timothée Poisot](https://github.com/tpoisot) - [★](https://github.com/ReScience/ReScience-submission/pull/11)[★](https://github.com/ReScience/ReScience-submission/pull/15) - Computational Ecology - Python, R, Julia - ORCID: [0000-0002-0735-5184](http://orcid.org/0000-0002-0735-5184) - - [Département de Sciences Biologiques](http://bio.umontreal.ca/nc/accueil/) - [Université de Montréal](http://www.umontreal.ca) — - Montréal, Canada - - -* [Karthik Ram](https://github.com/karthik) - [★](https://github.com/ReScience/ReScience-submission/pull/11)[★](https://github.com/ReScience/ReScience-submission/pull/39) - Ecology - Data Science, R - ORCID: [0000-0002-0233-1757](http://orcid.org/0000-0002-0233-1757) - - [Berkeley' Institute for Data Science](https://bids.berkeley.edu) - [Berkeley University of California](http://www.berkeley.edu) — - Berkeley, California, USA - - -* [Olivia Guest](https://github.com/oliviaguest) - [★](https://github.com/ReScience/ReScience-submission/pull/21)[★](https://github.com/ReScience/ReScience-submission/pull/30)[★](https://github.com/ReScience/ReScience-submission/pull/47) - Computational Cognitive Neuroscience, Cognitive Modelling - Python, C - ORCID: [0000-0002-1891-0972](http://orcid.org/0000-0002-1891-0972) - - [Department of Experimental Psychology](https://www.ucl.ac.uk/pals/research/experimental-psychology/) - [University College London](http://www.ucl.ac.uk) — - London, United Kingdom - - -* [Lorena Barba](https://github.com/labarba) - Computational Fluid Dynamics, High-Performance Computing, Biophysics - Python, CUDA - ORCID: [0000-0001-5812-2711](http://orcid.org/0000-0001-5812-2711) - - [Department of Mechanical and Aerospace Engineering](https://www.mae.seas.gwu.edu/) - [George Washington University](https://www.gwu.edu) — - Washington, D.C., USA - - -* [Benoît Girard](https://github.com/benoit-girard) - [★](https://github.com/ReScience/ReScience-submission/pull/3)[★](https://github.com/ReScience/ReScience-submission/pull/22)[★](https://github.com/ReScience/ReScience-submission/pull/33)[★](https://github.com/ReScience/ReScience-submission/pull/43)[★](https://github.com/ReScience/ReScience-submission/pull/47) - Computational Neuroscience, Robotics - Python, C - ORCID: [0000-0002-8117-7064](http://orcid.org/0000-0002-8117-7064) - - [Institut des Systèmes Intelligents et de Robotiques](http://www.isir.upmc.fr) - [Université Pierre et Marie Curie](http://www.upmc.fr) — Paris, France - - -## Reviewers - -* [Mehdi Khamassi](https://github.com/MehdiKhamassi) - [★](https://github.com/ReScience/ReScience-submission/pull/3) - Computational Neuroscience, Robotics - Python, C/C++, Matlab - ORCID: [0000-0002-2515-1046](http://orcid.org/0000-0002-2515-1046) - - -* [Cyrille Rossant](https://github.com/rossant) - [★](https://github.com/ReScience/ReScience-submission/pull/18) - Neurophysiological Data Analysis - Python, C - ORCID: [0000-0003-2069-9093](http://orcid.org/0000-0003-2069-9093) - -* [Georgios Detorakis](https://github.com/gdetor) - [★](https://github.com/ReScience/ReScience-submission/pull/14)[★](https://github.com/ReScience/ReScience-submission/pull/24) - Computational Neuroscience, Signal Processing - Python, C, Matlab, Fortran - ORCID: [0000-0001-5891-1702](http://orcid.org/0000-0001-5891-1702) - -* [Dirk Eddelbuettel](https://github.com/eddelbuettel) - Econometrics, Statistics, Data Science - R, C/C++ - ORCID: [0000-0001-6419-907X](http://orcid.org/0000-0001-6419-907X) - -* [Federico Vaggi](https://github.com/FedericoV) - [★](https://github.com/ReScience/ReScience-submission/pull/15)[★](https://github.com/ReScience/ReScience-submission/pull/41) - Systems Biology - Python, Matlab, C - ORCID: [0000-0001-8100-158X](http://orcid.org/0000-0001-8100-158X) - -* [Ozan Caglayan](https://github.com/ozancaglayan) - [★](https://github.com/ReScience/ReScience-submission/pull/20) - Signal Processing, Neural Networks - Python, C/C++, R - ORCID: [0000-0002-5992-3470](https://orcid.org/0000-0002-5992-3470) - -* [Jan Hermann](https://github.com/azag0) - Computational Chemistry, Material Physics - Fortran, Python - ORCID: [---](http://orcid.org/) - -* [Gökcen Eraslan](https://github.com/gokceneraslan) - Computational Biology - Python, C, R - ORCID: [0000-0001-9579-2909](http://orcid.org/0000-0001-9579-2909) - -* [Andrew P. Davison](https://github.com/apdavison) - [★](https://github.com/ReScience/ReScience-submission/pull/17) - Computational Neuroscience - Python - ORCID: [0000-0002-4793-7541](http://orcid.org/0000-0002-4793-7541) - -* [Marc André Delsuc](https://github.com/delsuc) - Biophysics, NMR spectroscopy - Python - ORCID: [0000-0002-1400-5326](http://orcid.org/0000-0002-1400-5326) - -* [Yoav Ram](https://github.com/yoavram) - [★](https://github.com/ReScience/ReScience-submission/pull/15) - Evolutionary Biology, Population Genetics - Python, R - ORCID: [0000-0002-9653-4458](http://orcid.org/0000-0002-9653-4458) - -* [Leonardo Uieda](https://github.com/leouieda) - Geophysics - C, Python - ORCID: [0000-0001-6123-9515](http://orcid.org/0000-0001-6123-9515) - -* [Hans Ekkehard Plesser](https://github.com/heplesser) - [★](https://github.com/ReScience/ReScience-submission/pull/17)[★](https://github.com/ReScience/ReScience-submission/pull/35) - Computational Neuroscience, Stochastic Processes - Python, C++ - ORCID: [0000-0001-7843-5993](http://orcid.org/0000-0001-7843-5993) - -* [Etienne Roesch](https://github.com/eroesch) - [★](https://github.com/ReScience/ReScience-submission/pull/21) - Computational Neuroscience, Neuroimaging, Data Science - Python, C/C++, Matlab, R - ORCID: [0000-0002-8913-4173](http://orcid.org/0000-0002-8913-4173) - -* [Ilhan Polat](https://github.com/ilayn) - Control Theory - Matlab, Python - ORCID: [0000-0003-0096-7409](http://orcid.org/0000-0003-0096-7409) - -* [Pauline Barmby](https://github.com/PBarmby) - Astrophysics - Python, R, C - ORCID: [0000-0003-2767-0090](http://orcid.org/0000-0003-2767-0090) - -* [Dan McGlinn](https://github.com/dmcglinn) - [★](https://github.com/ReScience/ReScience-submission/pull/11)[★](https://github.com/ReScience/ReScience-submission/pull/39) - Ecology - R - ORCID: [0000-0003-2359-3526](http://orcid.org/0000-0003-2359-3526) - -* [Julien Vitay](https://github.com/vitay) - [★](https://github.com/ReScience/ReScience-submission/pull/14)[★](https://github.com/ReScience/ReScience-submission/pull/51) - Computational Neuroscience - Python, C++ - ORCID: [0000-0001-5229-2349](http://orcid.org/0000-0001-5229-2349) - -* [Hrvoje Stojic](https://github.com/hstojic) - Learning and Decision Making, Cognitive Modelling - R, Python - ORCID: [---](http://orcid.org/) - -* [Owen L. Petchey](https://github.com/opetchey) - Ecology - R - ORCID: [0000-0002-7724-1633](http://orcid.org/0000-0002-7724-1633) - -* [Xavier Hinaut](https://github.com/neuronalX) - [★](https://github.com/ReScience/ReScience-submission/pull/19)[★](https://github.com/ReScience/ReScience-submission/pull/47) - Computational Neuroscience, Machine Learning - Python, Matlab, Java, C - ORCID: [0000-0002-1924-1184](http://orcid.org/0000-0002-1924-1184) - -* [Marcel Stimberg](https://github.com/mstimberg) - [★](https://github.com/ReScience/ReScience-submission/pull/18)[★](https://github.com/ReScience/ReScience-submission/pull/43) - Computational Neuroscience - Python, C/C++ - ORCID: [0000-0002-2648-4790](http://orcid.org/0000-0002-2648-4790) - -* [Markus Pfeiffer](https://github.com/markuspf) - Discrete Mathematics - GAP, C, Haskell, Python, Idris - ORCID: [---](http://orcid.org/) - -* [Simon van Heeringen](https://github.com/simonvh) - Computational Biology, Epigenomics, Regulatory Motif Analysis - Python - ORCID: [0000-0002-0411-3219](http://orcid.org/0000-0002-0411-3219) - -* [Dominique Geffroy](https://github.com/dombrno) - Condensed Matter Physics, Financial Derivatives - Python, C++ - ORCID: [0000-0003-2785-2679](http://orcid.org/0000-0003-2785-2679) - -* [Joseph Stachelek](https://github.com/jsta) - Ecology - R, Python - ORCID: [0000-0002-5924-2464](https://orcid.org/0000-0002-5924-2464) - -* [Serge Stinckwich](https://github.com/SergeStinckwich) - Agent-based Modelling, Computational Epidemiology - C, Python, Pharo - ORCID: [0000-0002-8755-9848](http://orcid.org/0000-0002-8755-9848) - -* [Daniel Nüst](https://github.com/nuest) - Geoprocessing, Sensor Web, Geocomputation - Java, R - ORCID: [0000-0002-0024-5046](http://orcid.org/0000-0002-0024-5046) - -* [Pierre Enel](https://github.com/piero-le-fou) - [★](https://github.com/ReScience/ReScience-submission/pull/19) - Neurophysiology, Computational Neuroscience - Python, Matlab, C - ORCID: [0000-0001-8983-6223](http://orcid.org/0000-0001-8983-6223) - -* [Cesar B. Rocha](https://github.com/crocha700) - Physical Oceanography, Geophysical Fluid Dynamics - Python, C, Fortran - ORCID: [0000-0003-4063-5468](http://orcid.org/0000-0003-4063-5468) - -* [Kevin Mattheus Moerman](https://github.com/Kevin-Mattheus-Moerman) - Computational Soft Tissue Biomechanics, Image-based Modelling - Octave, Matlab - ORCID: [---](http://orcid.org/) - -* [David Garcia](https://github.com/dgarcia-eu) - Computational Social Science - R, Python - ORCID: [0000-0002-2820-9151](http://orcid.org/0000-0002-2820-9151) - -* [Olivier Grisel](https://github.com/ogrisel) - [★](https://github.com/ReScience/ReScience-submission/pull/20) - Machine Learning - Python - ORCID: [0000-0002-8226-4012](http://orcid.org/0000-0002-8226-4012) - -* [Almar Klein](https://github.com/almarklein) - [★](https://github.com/ReScience/ReScience-submission/pull/28) - (Medical) Image Processing - Python - ORCID: [0000-0002-9978-2780](http://orcid.org/0000-0002-9978-2780) - -* [Tarandeep Singh Kalra](https://github.com/tarankalra-usgs) - Computational Fluid Dynamics, Applied Aerodynamics, Ocean Modeling - Fortran, Python, C - ORCID: [---](http://orcid.org/) - -* [Philipp Boersch-Supan](https://github.com/pboesu) - [★](https://github.com/ReScience/ReScience-submission/pull/39) - Ecology, Biological Oceanography, Biogeography - R - ORCID: [0000-0001-6723-6833](http://orcid.org/0000-0001-6723-6833) - -* [Ben Marwick](https://github.com/benmarwick) - Archaeology, Geosciences, Social sciences - R - ORCID: [---](http://orcid.org/) - -* [Emmanuel Hadoux](https://github.com/ehadoux) - Decision Theory, Markov Models, Argumentation (Artificial Intelligence) - - C++, Java, Ruby - ORCID: [0000-0003-4303-7885](http://orcid.org/0000-0003-4303-7885) - -* [Dmitrii Pasechnik](https://github.com/dimpase) - Algebra and Geometry, Combinatorics, Graphs, Optimization - C, Python, Computer Algebra Systems - ORCID: [0000-0002-7557-6886](http://orcid.org/0000-0002-7557-6886) - -* [Niranj Chandrasekaran](https://github.com/niranjchandrasekaran) - Molecular Biophysics - Python, Perl - ORCID: [---](http://orcid.org/) - -* [Fabien C. Y. Benureau](https://github.com/benureau) - [★](https://github.com/ReScience/ReScience-submission/pull/24) - Machine Learning, Robotics, Computational Neuroscience - Python, Julia, Go - ORCID: [0000-0003-4083-4512](http://orcid.org/0000-0003-4083-4512) - -* [Damien Drix](https://github.com/damiendr) - [★](https://github.com/ReScience/ReScience-submission/pull/22)[★](https://github.com/ReScience/ReScience-submission/pull/51) - Computational Neuroscience, Machine Learning - Julia, Python - ORCID: [0000-0003-4107-5693](http://orcid.org/0000-0003-4107-5693) - -* [Kamil S Jaron](https://github.com/KamilSJaron) - [★](https://github.com/ReScience/ReScience-submission/pull/27) - Evolutionary biology - R, C/C++, python - ORCID: [0000-0003-1470-5450](http://orcid.org/0000-0003-1470-5450) - -* [Anne Urai](https://github.com/anne-urai) - [★](https://github.com/ReScience/ReScience-submission/pull/36) - Cognitive neuroscience, Decision Making, Vision Science - Matlab, Python, R - ORCID: [0000-0001-5270-6513](http://orcid.org/0000-0001-5270-6513) - -* [Vamsi Spandan](https://github.com/nadnaps) - Computational Fluid Dynamics, High Performance Computing - Fortran, Python - ORCID: [0000-0003-0107-4135](http://orcid.org/0000-0003-0107-4135) - -* [Christopher B. Cole](https://github.com/Chris1221) - Statistical Genetics - R, Matlab, Python, C++ - ORCID: [0000-0002-6733-633X](http://orcid.org/0000-0002-6733-633X) - -* [Qihong Lu](https://github.com/qihongl) - [★](https://github.com/ReScience/ReScience-submission/pull/36) - Cognitive Psychology, Neuroimaging, Neural Networks - Python, Matlab, R - ORCID: [0000-0002-0730-5240](http://orcid.org/0000-0002-0730-5240) - -* [Emmanuel Noutahi](https://github.com/maclandrol) - Computational Biology, Evolutionary biology - Python, Java, Matlab, JavaScript - ORCID: [0000-0001-5216-9703](http://orcid.org/0000-0001-5216-9703) - -* [Francisco Pina-Martins](https://github.com/StuntsPT) - Bioinformatics, Evolutionary Biology, Population Genetics/Genomics - Python - ORCID: [0000-0003-1836-397X](http://orcid.org/0000-0003-1836-397X) - -* [Kyle Niemeyer](https://github.com/kyleniemeyer) - Combustion, Chemical Kinetics, Computational Fluid Dynamics, HPC - Python, Fortran, CUDA, Matlab - ORCID: [0000-0003-4425-7097](http://orcid.org/0000-0003-4425-7097) - -* [Aaron Shifman](https://github.com/aaronshifman) - [★](https://github.com/ReScience/ReScience-submission/pull/30)[★](https://github.com/ReScience/ReScience-submission/pull/41) - Computational Biology - Python, Matlab/Octave, Javascript - ORCID: [0000-0003-2140-7590](orcid.org/0000-0003-2140-7590) - -* [Roman Yurchak](https://github.com/rth) - [★](https://github.com/ReScience/ReScience-submission/pull/28) - Signal Processing, Information Retrieval - Python, C - ORCID: [0000-0002-2565-4444](http://orcid.org/0000-0002-2565-4444) - -* [Matt G. Hall](https://github.com/soolijoo) - [★](https://github.com/ReScience/ReScience-submission/pull/25) - Diffusion Imaging and Simulation - Java, Python, C++ - ORCID: [0000-0002-9530-5477](http://orcid.org/0000-0002-9530-5477) - -* [Christoph Metzner](https://github.com/ChristophMetzner) - [★](https://github.com/ReScience/ReScience-submission/pull/33) - Computational Neuroscience - Python, Matlab, Neuron, Genesis, Auryn/C++ - ORCID: [0000-0002-5933-2101](http://orcid.org/0000-0002-5933-2101) - -* [Stephan Grein](https://github.com/stephanmg) - Computational Neuroscience, HPC platforms, Numerics - Java, C++, Lua, Python, Matlab, R - ORCID: [0000-0001-9524-6633](http://orcid.org/0000-0001-9524-6633) - -* [Patricio Reyes](https://github.com/pareyesv) - Operations Research - Python, R - ORCID: [---](http://orcid.org/) - -* [Pietro Marchesi](https://github.com/pietromarchesi) - [★](https://github.com/ReScience/ReScience-submission/pull/30)[★](https://github.com/ReScience/ReScience-submission/pull/45) - Computational Neuroscience, Information Theory - Python - ORCID: [0000-0001-5955-6909](http://orcid.org/0000-0001-5955-6909) - -* [Joshua Pritikin](https://github.com/jpritikin) - Quantitative Psychology - R, C/C++, Stan, Coffeescript, Python, Perl, Bash - ORCID: [0000-0002-9862-5484](http://orcid.org/0000-0002-9862-5484) - -* [Arnaud Legrand](https://github.com/alegrand) - Parallel Distributed HPC, Optimization, Evaluation, Simulation - C, R, Shell, Perl, Python - ORCID: [0000-0002-8415-1046](http://orcid.org/0000-0002-8415-1046) - -* [Ryan B. Harvey](https://github.com/nihonjinrxs) - Comp. Harmonic Analysis, Data Science/Engineering - R, Python, SQL, Bash/Shell, Java - ORCID: [0000-0002-0821-7605](https://orcid.org/0000-0002-0821-7605) - -* [Anya Vostinar](https://github.com/anyaevostinar) - [★](https://github.com/ReScience/ReScience-submission/pull/27) - Digital Evolution, Agent-based simulation - C++ (11, 14), Python, R - ORCID: [0000-0001-7216-5283](https://orcid.org/0000-0001-7216-5283) - -* [Milad H. Mobarhan](https://github.com/miladh) - Computational Neuroscience - Python, C++ - ORCID: [0000-0003-1144-8794](https://orcid.org/0000-0003-1144-8794) - -* [Max M. Losch](https://github.com/mlosch) - Computational Visual Neuroscience, Machine Learning - Python, Matlab, Java, C/C++ - ORCID: [0000-0001-6525-4528](https://orcid.org/0000-0001-6525-4528) - -* [Alexandra K. Diem](https://github.com/akdiem) - Vascular modelling, Neurovascular Coupling - Python, Matlab, C, Java, R, Bash - ORCID: [0000-0003-1719-1942](https://orcid.org/0000-0003-1719-1942) - -* [Jaime Arias](https://github.com/himito) - Formal Methods - Python, C/C++, VHDL, SystemVerilog - ORCID Number: [0000-0003-3019-4902](https://orcid.org/0000-0003-3019-4902) - -* [Dennis Goldschmidt](https://github.com/degoldschmidt) - [★](https://github.com/ReScience/ReScience-submission/pull/45) - Computational Neuroscience, Neurorobotics - Python, C/C++, Java, Octave - ORCID: [0000-0002-0603-7176](https://orcid.org/0000-0002-0603-7176) - -* [Aurélien Nioche](https://github.com/AurelienNioche) - Agent-based modelling - Python - ORCID: [0000-0002-0567-2637](https://orcid.org/0000-0002-0567-2637) - -* [Bruno Sciolla](https://github.com/bsciolla) - Deep learning, Image processing, Medical Imaging - Python, C++, Matlab - ORCID: [0000-0002-7720-1455](https://orcid.org/0000-0002-7720-1455) - -* [Vahid Rostami](https://github.com/Vahidrostami) - Computational Neuroscience, Statistical Neuroscience - Python - ORCID: [0000-0002-3851-0220](orcid.org/0000-0002-3851-0220) - -* [Tiina Manninen](https://github.com/TiinaManninen) - [★](https://github.com/ReScience/ReScience-submission/pull/33) - Computational Neuroscience - Matlab, Python - ORCID: [0000-0002-0456-1185](https://orcid.org/0000-0002-0456-1185) - -* [Shailesh Appukuttan](https://github.com/appukuttan-shailesh) - [★](https://github.com/ReScience/ReScience-submission/pull/43) - Computational Neuroscience, Neurophysiology, Smooth Muscle - HOC, NMODL, Python, PyNN - ORCID: [0000-0002-0148-8023](https://orcid.org/0000-0002-0148-8023) - -* [Hao Ye](https://github.com/ha0ye) - Ecology, Dynamic Systems - R, C++ - ORCID: [0000-0002-8630-1458](https://orcid.org/0000-0002-8630-1458) - -* [Paweł T. Jochym](https://github.com/jochym) - Computational Material Science, Theoretical Physics - Python, C/C++, Pascal, Fortran - ORCID: [0000-0003-0427-7333](https://orcid.org/0000-0003-0427-7333) - -* [Pritish Patil](https://github.com/iampritishpatil) - Computational Neurocience - Python (Neuron, Moose, Brian), Maltlab - ORCID: [0000-0002-2655-4090](orcid.org/0000-0002-2655-4090) - -* [Maarten Trompper](https://github.com/digitalheir) - Artificial Intelligence - Java, Javascript - ORCID: [0000-0003-1167-0432](https://orcid.org/0000-0003-1167-0432) - -* [Tania Allard](https://github.com/trallard) - Computational Materials Science, Biomaterials, Data Science - Python, R, C/C++, Fortran, Matlab - ORCID: [0000-0002-5353-5397](https://orcid.org/0000-0002-5353-5397) - -* [Romain Cazé](https://github.com/rcaze) - Computational Neuroscience - Python - ORCID: [0000-0002-7798-3696](https://orcid.org/0000-0002-7798-3696) - -* [Junpeng Lao](https://github.com/junpenglao) - Computational Neuroscience, Bayesian Statistics - Python, Matlab - ORCID: [0000-0001-6029-7510]( https://orcid.org/0000-0001-6029-7510) - -* [Geoff LaFlair](www.github.com/gtlaflair) - Language assessment, Corpus linguistics, Second language research, Applied linguistics - R - ORCID: [0000-0003-0306-6550](https://orcid.org/0000-0003-0306-6550) - -* [Arindam Basu](https://github.com/arinbasu) - Epidemiology, Medicine, Environmental Health - R, Python, Stata - ORCID: [0000-0003-2326-2292](https://orcid.org/0000-0003-2326-2292) - -* [Nikolaos Efthymiou](https://github.com/NikEfth) - Medical Imaging, Positron Emission Tomography (PET) - C/C++, Python, Matlab - ORCID: [0000-0003-1947-5033]( https://orcid.org/0000-0003-1947-5033) - -* [Xuedong Shang](https://github.com/xuedong) - Reinforcement Learning, Machine Learning, Optimization - Python, Julia, Matlab, OCaml, R, C/C++ - ORCID: [0000-0002-1537-6540](https://orcid.org/0000-0002-1537-6540) - -* [Dan Kortschak](https://github.com/kortschak) - Genomics - Go - ORCID: [0000-0001-8295-2301](https://orcid.org/0000-0001-8295-2301) - - -* [Konstantinos Chatzilygeroudis](https://github.com/costashatz) - Reinforcement Learning, Control, Gaussian Processes, Optimization - C++, C, Python, Matlab/Octave, Scala - ORCID: [0000-0003-3585-1027](https://orcid.org/0000-0003-3585-1027) - -* [Thiago Mosqueiro](https://github.com/thmosqueiro) - Computational Neuroscience, Machine Learning, Statistical Physics, Biology - Python, Fortran, C/C++, R, Octave (Matlab), Scala - ORCID: [0000-0001-5808-8189](https://orcid.org/0000-0001-5808-8189) - -* [Miguel P Xochicale](https://github.com/mxochicale) - Human-Robot Interaction, Nonlinear Time Series Analysis, Signal Processing, - R, Python, Octave, C/C++, Fortran -ORCID: [0000-0002-8225-7517](https://orcid.org/0000-0002-8225-7517) - -* [Christian Jarvers](https://github.com/cJarvers) - Computational Neuroscience, Machine Learning/Deep Learning - Python, Octave/Matlab, Julia, Fortran - ORCID: [0000-0003-0062-9776](https://orcid.org/0000-0003-0062-9776) - - -* [Abdulqawi Saif](https://github.com/LeUnAiDeS) - Distributed Systems, Scalable Databases, Big Data Analytics, Software Verification and Validation - Java, C++, Ruby, OCL, JML, R - ORCID: [0000-0003-3537-2499](https://orcid.org/0000-0003-3537-2499) - -* [Chris Rackauckas](https://github.com/ChrisRackauckas) - Systems Biology, Dynamical systems, Statistics - Julia, Matlab, Mathematica, C/C++, R, Python - ORCID: [0000-0001-5850-0663](https://orcid.org/0000-0001-5850-0663) - -* [Rui Portela](https://github.com/ruimcportela) - Systems and Synthetic Biology, Machine Learning - Python, Matlab, R, SQL - ORCID: [0000-0002-3627-6477](https://orcid.org/0000-0002-3627-6477) - -* [Eric Berquist](https://github.com/berquist) - Computational Chemistry and Spectroscopy - Python, C++ - ORCID: [0000-0001-8186-9522](https://orcid.org/0000-0001-8186-9522) - -* [Josh Gardner](https://github.com/jpgard) - Machine Learning, Education - Python, R - ORCID: [0000-0002-4998-5918](https://orcid.org/0000-0002-4998-5918) - -* [Nicolás Guarín-Zapata](https://github.com/nicoguaro) - Computational & Solid Mechanics, Wave Propagation- Python, Matlba, Fortran - ORCID: [0000-0002-9435-1914](https://orcid.org/0000-0002-9435-1914) - -* [Frank Förster](https://github.com/greatfireball) - Bioinformatics, Computational Biology, Phylogenetics, Genomics, Transcriptomics - Perl, R, Python, PHP, GNU/Linux, Shell - ORCID: [0000-0003-4166-5423](https://orcid.org/0000-0003-4166-5423) - -* [Travis Hinkelman](https://github.com/hinkelman) - Ecology - R, NetLogo - ORCID: [0000-0002-8157-8407](https://orcid.org/0000-0002-8157-8407) - -* [Inderdeep Singh Bajwa](https://github.com/InderdeepBajwa/) - Machine Learning, Artificial Intelligence, Computer Vision - Python, C++, Julia, Golang, C# - ORCID: [0000-0003-3878-8166](https://orcid.org/0000-0003-3878-8166/) - -* [Dylan Aïssi](https://github.com/daissi/) -Bioinformatics, Computational Biology, Epigenomics, Genomics, Transcriptomics - R, Shell, Python, Perl, Julia - ORCID: [0000-0002-5858-6468](https://orcid.org/0000-0002-5858-6468) - -* [Manjari Narayan](https://github.com/mnarayan) -Applied and Computational Statistics, Machine Learning, Computational Neuroscience, Neuroimaging - Python, Matlab/Octave, R -ORCID: [0000-0001-5348-270X](https://orcid.org/0000-0001-5348-270X) - -* [Garrett Smith](https://github.com/garrett-m-smith) -Psycholinguistics, cognitive modeling, dynamical systems - Python, R, Matlab/Octave -ORCID: [0000-0001-7238-3942](https://orcid.org/0000-0001-7238-3942) - diff --git a/05-FAQ.md b/05-FAQ.md deleted file mode 100644 index fa74305..0000000 --- a/05-FAQ.md +++ /dev/null @@ -1,198 +0,0 @@ ---- -layout: page -menutitle: FAQ -permalink: /faq/ ---- - -# Frequently Asked Questions - -If your question is not answered below, please -[create an issue](https://github.com/ReScience/ReScience/issues) on GitHub and -ask it there. - -## Can I help? - -Yes ! You can: - - * Become a reviewer by [filling your information](https://github.com/ReScience/ReScience/issues/27) and [watch](https://github.com/ReScience/ReScience-submission/subscription) for new submission - * [Submit](../write) paper for the work you've already replicated - * Spread the word about Re**Science** in your community - ([twitter](http://twitter.com/ReScienceEds), mailing lists, blogs, etc.) - * [Star the project](https://github.com/ReScience/ReScience) on GitHub - * Help improving this website by - [forking it](https://github.com/ReScience/rescience.github.io/fork) and - propose modifications (through PR) - * [Opening an issue](https://github.com/ReScience/ReScience/issues) if you - have any unanswered question. - * The [Website](https://github.com/ReScience/rescience.github.io) could certainly - use the help of a [Jekyll](http://jekyllrb.com) expert and the eye of a - designer (but keep in mind we want to keep a simple & clean website where - content is the primary focus)... - * Print stickers from the - [Re**Science** material repository](https://github.com/ReScience/ReScience-material) - (and possibly send some to us...) - - -## What's the difference between replication and reproduction? - -There is no concensus yet on what exactly these two terms mean, so -here is how we understand and use them. - -Reproduction of a computational study means running the same -computation on the same input data, and then checking if the results -are the same, or at least "close enough" when it comes to numerical -approximations. Reproduction can be considered as software testing at -the level of a complete study. - -Replication of a scientific study (computational or other) means -repeating a published protocol, respecting its spirit and intentions -but varying the technical details. For computational work, this would -mean using different software, running a simulation from different -initial conditions, etc. The idea is to change something that everyone -believes shouldn't matter, and see if the scientific conclusions are -affected or not. - -Reproduction verifies that a computation was recorded with enough -detail that it can be analyzed later or by someone else. Replication -explores which details matter for reaching a specific scientific -conclusion. A replication attempt is most useful if reproducibility -has already been verified. Otherwise, if replication fails, leads to -different conclusions, you cannot trace back the differences in the -results to the underlying code and data. - -In the ideal world, the reproducibility of computational studies would -be checked automatically before publication. In the real world, most -published studies do not even claim to be reproducible, because the code -or the input data are not made public. Given this situation, -a Re**Science** publication provides two important services: by replicating -the original work, it provides an independent implementation of the -original computational protocol, and by making this new implementation -public, it is reproducible and thus a safer basis for future research -to build on. - - -## Are there any publication fees? - -No. Re**Science** promotes open access and relies on the volunteer work of -editors and reviewers. And the free hosting by GitHub. - - -## Can I submit a paper using proprietary tools such as Matlab? - -No. If we aim at replicability, we have to make sure the proposed -implementation allows anyone to re-run and understand the code without any -barriers. Proprietary software constitutes such a barrier because of their -price and their closed nature. -An implementation specifically targeting a free alternative such as -[Octave](https://www.gnu.org/software/octave/) will be accepted though. - - -## Is it mandatory to have an open-source license on the code? - -Yes. The code accompanying Re**Science** articles will be archived at -[Zenodo](https://zenodo.org/) along with the article and data, entirely under open -licenses. This is part of the open access principle underlying Re**Science**. For the -choice of a license for the code, we refer to the [the Debian Free Software -Guidelines](https://www.debian.org/social_contract#guidelines). - - -## Can I submit the replication of my own research? - -No. Mistakes in the implementation of research questions and methods are often -due to biases authors invariably have, consciously or not. One's biases will -inevitably carry over to how one approaches a replication. Perhaps even more importantly, -we aim at the cross-fertilization of research and trying to replicate the work of one's -peers might pave the way for a future collaboration, or may give rise to new ideas as -a result of the replication effort. - - -## Can I suggest a replication? - -Yes. If you want to suggest an article for a replication, just -[open a new issue](https://github.com/ReScience/call-for-replication/issues/new) -in the [call for replication repository](https://github.com/ReScience/call-for-replication) and give the reference of the original -article and possibly the reason you would like to see this article replicated -(please refrain from suggesting your own work). Note that you're also -encouraged to register as a reviewer such that you can review the replication -you've been proposing if someone actually takes up the challenge. - -If you're looking for some challenge, you can also look at the -[current list of suggestions](https://github.com/ReScience/call-for-replication/issues). - - -## If my submission is rejected, can I resubmit it? - -This depends on the reason your submission was rejected. If the -original research has already been replicated previously (in -Re**Science** or elsewhere), it is unlikely we'll consider another replication, even if you -think your implementation is better. However, if your submission has ben -rejected because reviewers cannot make it run, you are encouraged to re-submit -once the identified problems have been solved. - - -## What if I fail to replicate a research result? - -Some research may not be replicable. Before declaring a -research result non-replicable, we require extra caution to be taken. In addition -to scrutiny of your submission by reviewers and editors, we will contact the -authors of the original research, and issue a challenge to the Re**Science** -community to spot and report (using the issue tracker) errors in your implementation. -If no errors are found, your work will be accepted and -the original research will be declared non-replicable. - - -## Is there a preferred implementation language? - -We favor a Python implementation because this language offers a -[scientific programming stack](http://www.scipy.org) that can handle research in many -domains of science (see for example the [Scipy 2015](http://scipy2015.scipy.org) -and [EuroScipy 2015](https://www.euroscipy.org/2015/) conferences). Python is -also often reported by scientists to easier to learn and use than other languages. -Furthermore, using Python might allow us to use -the [IPython](http://ipython.org) notebook and the upcoming -[Jupyter](https://jupyter.org) environments. - -However, other languages or tools are acceptable if they are mainstream in the -respective domain of research. - -## I'm a student, can I submit? - -**Yes ! Students are strongly encouraged to submit their work**. Although the -Re**Science** publishing model is a bit different from other academic journals, -it can give students a first experience at peer-reviewed scholarly publishing, including -meeting standards of scientific rigor and addressing reviewers' comments. Publishing -in Re**Science** is also a way to actively contribute to open science while adding to one's -publication record. - - -## How do I know if my replication is successful? - -This depends mainly on the original paper introducing the research results to be -replicated. Results might be presented in a qualitative or quantitative way and you'll have to -clearly state why you think your implementation of a method or protocol is a faithful replication -of the original results. - - -## What kind of research can I replicate? - -Any computational research in any domain of science as long as there is an -editor from the [Board](../board) who has the expertise to edit your submission. The editorial -board is growing to increase the scientific domains being covered. If no editor is -able to edit your submission, you can also propose a guest editor (who must -be willing to work with our GitHub-based editorial processes). - - -## Does ReScience issue DOIs (Digital Object Identifiers)? - -Re**Science** itself does not, but every article published in Re**Science** receives a DOI from, and is -indexed in [Zenodo](https://zenodo.org/collection/user-rescience). - - -## What is the preferred format for the accompanying article? - -We use **exclusively** Markdown format, from which articles are converted to -HTML, PDF, and other formats using [pandoc](http://johnmacfarlane.net/pandoc/). - -We realize that this may impose some limitations on formatting possibilities. -However, it is the tradeoff we chose to be able to offer a green open-access journal. -All editors and reviewers are volunteers, and we want to minimize their workload. diff --git a/06-platform-instruction.md b/06-platform-instruction.md deleted file mode 100644 index 7918b29..0000000 --- a/06-platform-instruction.md +++ /dev/null @@ -1,107 +0,0 @@ ---- -layout: page -permalink: /platform/ ---- - -# Provide platform information - -Submissions to ReScience come with code. We ask information about the platform that was used -to run the code, the detail depending on the tools and programming languages used. - -This information will be included in the file `code/README.md` of the submission. Consider -the whole execution pipeline for your results for possible additional tools (e.g. Bash, -random number generator, etc). - -## Version information for Python - -For Python, NumPy, SciPy and matplotlib (common Python dependencies), the -following script will provide detailed information on your platform. - -```py -from __future__ import print_function -import sys -import platform - -print("Platform:", sys.platform) -print("Python:", sys.version) -print("Machine and architecture", platform.machine(), *platform.architecture()) - -try: - import numpy as np - print("NumPy:", np.version.version) -except: - pass - -try: - import scipy - print("SciPy:", scipy.version.version) -except: - pass - -try: - import matplotlib - print("matplotlib:", matplotlib.__version__) -except: - pass -``` - -The output, for instance - -``` -Platform: linux -Python: 3.5.2+ (default, Sep 22 2016, 12:18:14) -[GCC 6.2.0 20160914] -Machine and architecture x86_64 64bit ELF -NumPy: 1.12.0 -SciPy: 0.18.1 -matplotlib: 2.0.0 -``` - -Note that the versions of NumPy, SciPy and matplotlib should be given if they are used only -and that the version of any other library that is not part of Python's standard library -should also be given. - -## Version information for compiled languages - -For compiled languages, the important information consists in the platform, the -compiler, its version, and the compiler flags. - -We provide below an example for the C language on Unix-like platforms. Modify it to suit -your project and feel free to contact ReScience via the GitHub issues or Twitter if you need -further assistance. - -Platform information: - -``` -uname -mosv -``` - -``` -Linux #1 SMP Debian 3.16.7-ckt9-3 (2015-04-23) x86_64 GNU/Linux -``` - -Hardware information: -``` -grep -E '(^model name|^vendor_id|^flags)' /proc/cpuinfo | sort | uniq -``` - -``` -flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm ida arat epb xsaveopt pln pts dtherm tpr_shadow vnmi flexpriority ept vpid fsgsbase smep erms -model name : Intel(R) Core(TM) i5-3230M CPU @ 2.60GHz -vendor_id : GenuineIntel -``` - -Compiler information for C: -``` -gcc --version -``` - -``` -gcc (Debian 6.2.0-5) 6.2.0 20160927 -Copyright (C) 2016 Free Software Foundation, Inc. -This is free software; see the source for copying conditions. There is NO -warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. -``` - -with compilation flags ```-O3 -std=c99```. - diff --git a/Gemfile b/Gemfile index 46d62ea..bc5a7f5 100644 --- a/Gemfile +++ b/Gemfile @@ -1,4 +1,6 @@ source 'https://rubygems.org' + gem "jekyll" gem 'redcarpet' gem 'github-pages' +gem "jekyll-scholar" diff --git a/Gemfile.lock b/Gemfile.lock new file mode 100644 index 0000000..ffb2f26 --- /dev/null +++ b/Gemfile.lock @@ -0,0 +1,293 @@ +GEM + remote: https://rubygems.org/ + specs: + activesupport (7.1.2) + base64 + bigdecimal + concurrent-ruby (~> 1.0, >= 1.0.2) + connection_pool (>= 2.2.5) + drb + i18n (>= 1.6, < 2) + minitest (>= 5.1) + mutex_m + tzinfo (~> 2.0) + addressable (2.8.5) + public_suffix (>= 2.0.2, < 6.0) + base64 (0.2.0) + bibtex-ruby (4.4.7) + latex-decode (~> 0.0) + bigdecimal (3.1.4) + citeproc (1.0.10) + namae (~> 1.0) + citeproc-ruby (1.1.14) + citeproc (~> 1.0, >= 1.0.9) + csl (~> 1.6) + coffee-script (2.4.1) + coffee-script-source + execjs + coffee-script-source (1.11.1) + colorator (1.1.0) + commonmarker (0.23.10) + concurrent-ruby (1.2.2) + connection_pool (2.4.1) + csl (1.6.0) + namae (~> 1.0) + rexml + csl-styles (1.0.1.11) + csl (~> 1.0) + dnsruby (1.70.0) + simpleidn (~> 0.2.1) + drb (2.2.0) + ruby2_keywords + em-websocket (0.5.3) + eventmachine (>= 0.12.9) + http_parser.rb (~> 0) + ethon (0.16.0) + ffi (>= 1.15.0) + eventmachine (1.2.7) + execjs (2.9.1) + faraday (2.7.12) + base64 + faraday-net_http (>= 2.0, < 3.1) + ruby2_keywords (>= 0.0.4) + faraday-net_http (3.0.2) + ffi (1.16.3) + forwardable-extended (2.6.0) + gemoji (3.0.1) + github-pages (228) + github-pages-health-check (= 1.17.9) + jekyll (= 3.9.3) + jekyll-avatar (= 0.7.0) + jekyll-coffeescript (= 1.1.1) + jekyll-commonmark-ghpages (= 0.4.0) + jekyll-default-layout (= 0.1.4) + jekyll-feed (= 0.15.1) + jekyll-gist (= 1.5.0) + jekyll-github-metadata (= 2.13.0) + jekyll-include-cache (= 0.2.1) + jekyll-mentions (= 1.6.0) + jekyll-optional-front-matter (= 0.3.2) + jekyll-paginate (= 1.1.0) + jekyll-readme-index (= 0.3.0) + jekyll-redirect-from (= 0.16.0) + jekyll-relative-links (= 0.6.1) + jekyll-remote-theme (= 0.4.3) + jekyll-sass-converter (= 1.5.2) + jekyll-seo-tag (= 2.8.0) + jekyll-sitemap (= 1.4.0) + jekyll-swiss (= 1.0.0) + jekyll-theme-architect (= 0.2.0) + jekyll-theme-cayman (= 0.2.0) + jekyll-theme-dinky (= 0.2.0) + jekyll-theme-hacker (= 0.2.0) + jekyll-theme-leap-day (= 0.2.0) + jekyll-theme-merlot (= 0.2.0) + jekyll-theme-midnight (= 0.2.0) + jekyll-theme-minimal (= 0.2.0) + jekyll-theme-modernist (= 0.2.0) + jekyll-theme-primer (= 0.6.0) + jekyll-theme-slate (= 0.2.0) + jekyll-theme-tactile (= 0.2.0) + jekyll-theme-time-machine (= 0.2.0) + jekyll-titles-from-headings (= 0.5.3) + jemoji (= 0.12.0) + kramdown (= 2.3.2) + kramdown-parser-gfm (= 1.1.0) + liquid (= 4.0.4) + mercenary (~> 0.3) + minima (= 2.5.1) + nokogiri (>= 1.13.6, < 2.0) + rouge (= 3.26.0) + terminal-table (~> 1.4) + github-pages-health-check (1.17.9) + addressable (~> 2.3) + dnsruby (~> 1.60) + octokit (~> 4.0) + public_suffix (>= 3.0, < 5.0) + typhoeus (~> 1.3) + html-pipeline (2.14.3) + activesupport (>= 2) + nokogiri (>= 1.4) + http_parser.rb (0.8.0) + i18n (1.14.1) + concurrent-ruby (~> 1.0) + jekyll (3.9.3) + addressable (~> 2.4) + colorator (~> 1.0) + em-websocket (~> 0.5) + i18n (>= 0.7, < 2) + jekyll-sass-converter (~> 1.0) + jekyll-watch (~> 2.0) + kramdown (>= 1.17, < 3) + liquid (~> 4.0) + mercenary (~> 0.3.3) + pathutil (~> 0.9) + rouge (>= 1.7, < 4) + safe_yaml (~> 1.0) + jekyll-avatar (0.7.0) + jekyll (>= 3.0, < 5.0) + jekyll-coffeescript (1.1.1) + coffee-script (~> 2.2) + coffee-script-source (~> 1.11.1) + jekyll-commonmark (1.4.0) + commonmarker (~> 0.22) + jekyll-commonmark-ghpages (0.4.0) + commonmarker (~> 0.23.7) + jekyll (~> 3.9.0) + jekyll-commonmark (~> 1.4.0) + rouge (>= 2.0, < 5.0) + jekyll-default-layout (0.1.4) + jekyll (~> 3.0) + jekyll-feed (0.15.1) + jekyll (>= 3.7, < 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+ safe_yaml (1.0.5) + sass (3.7.4) + sass-listen (~> 4.0.0) + sass-listen (4.0.0) + rb-fsevent (~> 0.9, >= 0.9.4) + rb-inotify (~> 0.9, >= 0.9.7) + sawyer (0.9.2) + addressable (>= 2.3.5) + faraday (>= 0.17.3, < 3) + simpleidn (0.2.1) + unf (~> 0.1.4) + terminal-table (1.8.0) + unicode-display_width (~> 1.1, >= 1.1.1) + typhoeus (1.4.1) + ethon (>= 0.9.0) + tzinfo (2.0.6) + concurrent-ruby (~> 1.0) + unf (0.1.4) + unf_ext + unf_ext (0.0.9.1) + unicode-display_width (1.8.0) + +PLATFORMS + ruby + +DEPENDENCIES + github-pages + jekyll + jekyll-scholar + redcarpet + +BUNDLED WITH + 2.1.4 diff --git a/README.md b/README.md deleted file mode 100644 index 1987843..0000000 --- a/README.md +++ /dev/null @@ -1,24 +0,0 @@ -[![Build Status](https://travis-ci.org/ReScience/rescience.github.io.svg?branch=master)](https://travis-ci.org/ReScience/rescience.github.io) - -# ReScience website - -### Website - -http://rescience.github.io - -### Serve locally - -``` -bundle exec jekyll serve -``` - -### Force rebuild on GitHub -``` -bundle exec htmlproof ./_site --only-4xx --check-favicon --check-html -``` - -### Check website - -``` -bundle exec htmlproof ./_site --only-4xx --check-favicon --check-html -``` diff --git a/_config.yml b/_config.yml deleted file mode 100644 index 7c328d9..0000000 --- a/_config.yml +++ /dev/null @@ -1,16 +0,0 @@ -# Site settings -title: The ReScience Journal -# email: your-email@domain.com -description: Reproducible Science is good.
- Replicated Science is better. -baseurl: "" # the subpath of your site, e.g. /blog/ -url: "http://rescience.github.io" # the base hostname & protocol for your site -twitter_username: ReScienceEds -github_username: ReScience - -# Build settings -markdown: kramdown - - -# Exclude: -exclude: ["README.md"] diff --git a/_includes/footer.html b/_includes/footer.html deleted file mode 100644 index df3e1cb..0000000 --- a/_includes/footer.html +++ /dev/null @@ -1,28 +0,0 @@ - diff --git a/_includes/head.html b/_includes/head.html deleted file mode 100644 index 09237b5..0000000 --- a/_includes/head.html +++ /dev/null @@ -1,17 +0,0 @@ - - - - - - - - - {% if page.title %}{{ page.title }}{% else %}{{ site.title }}{% endif %} - - - - - - diff --git a/_includes/header.html b/_includes/header.html deleted file mode 100644 index 59634b3..0000000 --- a/_includes/header.html +++ /dev/null @@ -1,27 +0,0 @@ -
- -
- - The ReScience Journal - - - -
- -
diff --git a/_layouts/default.html b/_layouts/default.html deleted file mode 100644 index e4ab96f..0000000 --- a/_layouts/default.html +++ /dev/null @@ -1,20 +0,0 @@ - - - - {% include head.html %} - - - - {% include header.html %} - -
-
- {{ content }} -
-
- - {% include footer.html %} - - - - diff --git a/_layouts/index.html b/_layouts/index.html deleted file mode 100644 index 444fa17..0000000 --- a/_layouts/index.html +++ /dev/null @@ -1,22 +0,0 @@ ---- -layout: default ---- -
- -
- {{ content }} -
- - - -
diff --git a/_layouts/page.html b/_layouts/page.html deleted file mode 100644 index 10bdbb8..0000000 --- a/_layouts/page.html +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: default ---- -
- - - -
- {{ content }} -
- -
diff --git a/_layouts/post.html b/_layouts/post.html deleted file mode 100644 index a2b4e52..0000000 --- a/_layouts/post.html +++ /dev/null @@ -1,15 +0,0 @@ ---- -layout: default ---- -
- -
-

{{ page.title }}

-

{{ page.date | date: "%b %-d, %Y" }}{% if page.author %} • {{ page.author }}{% endif %}{% if page.meta %} • {{ page.meta }}{% endif %}

-
- -
- {{ content }} -
- -
diff --git a/_layouts/read.html b/_layouts/read.html deleted file mode 100644 index bbe91c6..0000000 --- a/_layouts/read.html +++ /dev/null @@ -1,36 +0,0 @@ ---- -layout: default ---- -
- -
- {{ content }} -
- - - -
diff --git a/_posts/2015-08-14-Topalidou-Rougier.md b/_posts/2015-08-14-Topalidou-Rougier.md deleted file mode 100644 index be1b97c..0000000 --- a/_posts/2015-08-14-Topalidou-Rougier.md +++ /dev/null @@ -1,18 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Interaction between cognitive and motor cortico-basal - ganglia loops during decision making: a computational study" -date: 2015-08-14 -categories: neuroscience python -author: Meropi Topalidou & Nicolas P. Rougier -volume: 1 -issue: 1 -doi: 10.5281/zenodo.27944 -pdf: https://github.com/ReScience-Archives/ReScience-Entry-Topalidou-Rougier-2015/raw/1.0/article/article.pdf -repository: https://github.com/ReScience-Archives/ReScience-Entry-Topalidou-Rougier-2015 -review: https://github.com/ReScience/ReScience-submission/pull/3 -zenodo: https://zenodo.org/record/27944 -keywords: neuroscience, basal ganglia, python ---- - diff --git a/_posts/2015-09-01-journal-start.md b/_posts/2015-09-01-journal-start.md deleted file mode 100644 index edb38db..0000000 --- a/_posts/2015-09-01-journal-start.md +++ /dev/null @@ -1,13 +0,0 @@ ---- -layout: post -type: news -title: Official creation -date: 2015-09-01 -categories: news ---- - -It's our great pleasure to announce the creation of Re**Science** which is a -peer-reviewed journal that targets computational research and encourages the -explicit replication of already published research, promoting new and -open-source implementations in order to ensure that the original research is -reproducible. diff --git a/_posts/2015-09-06-LabCritics.md b/_posts/2015-09-06-LabCritics.md deleted file mode 100644 index 37c74a3..0000000 --- a/_posts/2015-09-06-LabCritics.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "ReScience: A Scientific Journal Living on Github" -date: 2015-09-06 -categories: news ---- - -[LabCritics](http://www.labcritics.com) kindly made a [post](http://www.labcritics.com/rescience-a-scientific-journal-with-github-at-its-core-4729/?utm_source=@labcritics) introducing Re**Science** and explaining its goals: "Computational research is set to get new open source journal solely for publishing implementations of algorithms and codes already published. Termed ReScience (Replicated Science – I guess [**note**: yes]), the journal uses and exists solely on Github, a popular Web-based Git repository service, offering all of the distributed revision control and source code management functionality of Git." - diff --git a/_posts/2015-09-06-ReviewTest.md b/_posts/2015-09-06-ReviewTest.md deleted file mode 100644 index 3fbaa03..0000000 --- a/_posts/2015-09-06-ReviewTest.md +++ /dev/null @@ -1,13 +0,0 @@ ---- -layout: post -type: news -title: "Review process test is over" -date: 2015-08-10 -categories: news ---- - -We've been testing the -[review process](https://github.com/ReScience/ReScience-submission/pull/3) with -Tiziano Zito (editor), Benoît Girard (reviewer) and Mehdi Khamassi -(reviewer). They helped smoothing the whole process and we're ready for mass -production! But let's wait for a second review... diff --git a/_posts/2016-01-07-NewYear.md b/_posts/2016-01-07-NewYear.md deleted file mode 100644 index b715dcc..0000000 --- a/_posts/2016-01-07-NewYear.md +++ /dev/null @@ -1,13 +0,0 @@ ---- -layout: post -type: news -title: "New year, new challenges ahead" -date: 2016-01-07 -categories: news ---- - -Even though open and reproducible science is gaining fast ground, there still -exists a large number of published computational researches that are just -awaiting replication. Why not pick your favorite paper and try to replicate it -? If you're interested in this specific paper, chances are that your replication -will also be interesting for a lot of researchers. diff --git a/_posts/2016-02-10-Viejo-Girard-Khamassi.md b/_posts/2016-02-10-Viejo-Girard-Khamassi.md deleted file mode 100644 index fb5f0bb..0000000 --- a/_posts/2016-02-10-Viejo-Girard-Khamassi.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Speed/accuracy trade-off between the habitual and the - goal-directed process" -date: 2016-02-10 -categories: neuroscience python -author: Guillaume Viejo, Benoît Girard & Mehdi Khamassi -volume: 2 -issue: 1 -doi: 10.5281/zenodo.45852 -pdf: https://github.com/ReScience-Archives/Viejo-Girard-Khamassi-2016/raw/master/article/viejo_girard_khamassi.pdf -repository: https://github.com/ReScience-Archives/Viejo-Girard-Khamassi-2016 -review: https://github.com/ReScience/ReScience-submission/pull/14 -zenodo: https://zenodo.org/record/45852 -keywords: neuroscience, decision making, python ---- diff --git a/_posts/2016-03-07-Stachelek.md b/_posts/2016-03-07-Stachelek.md deleted file mode 100644 index 35e4346..0000000 --- a/_posts/2016-03-07-Stachelek.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Least-cost modelling on irregular landscape graphs" -date: 2016-03-07 -categories: ecology R -author: Joseph Stachelek -volume: 2 -issue: 1 -doi: 10.5281/zenodo.47146 -pdf: https://github.com/ReScience-Archives/Stachelek-2016/raw/master/article/article.pdf -repository: https://github.com/ReScience-Archives/Stachelek-2016/ -review: https://github.com/ReScience/ReScience-submission/pull/11 -zenodo: https://zenodo.org/record/47146 -keywords: Ecology, Least-cost path, Delaunay triangulation, Graph Theory ---- diff --git a/_posts/2016-04-22-Petchey-Plebany-Pennekamp.md b/_posts/2016-04-22-Petchey-Plebany-Pennekamp.md deleted file mode 100644 index 86e3804..0000000 --- a/_posts/2016-04-22-Petchey-Plebany-Pennekamp.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Chaos in a long-term experiment with a plankton community" -date: 2016-04-22 -categories: ecology R -author: Owen Petchey, Marco Plebani, Frank Pennekamp -volume: 2 -issue: 1 -doi: 10.5281/zenodo.50213 -pdf: https://github.com/ReScience-Archives/Petchey-Plebani-Pennekamp-2016/raw/master/article/article.pdf -repository: https://github.com/ReScience-Archives/Petchey-Plebani-Pennekamp-2016 -review: https://github.com/ReScience/ReScience-submission/pull/15 -zenodo: https://zenodo.org/record/50213 -keywords: Ecology, Forecasting, Prediction, Chaos, Nonlinear dynamics, Plankton community, Species interactions ---- diff --git a/_posts/2016-07-02-Reviewers.md b/_posts/2016-07-02-Reviewers.md deleted file mode 100644 index 305764d..0000000 --- a/_posts/2016-07-02-Reviewers.md +++ /dev/null @@ -1,14 +0,0 @@ ---- -layout: post -type: news -title: "You can help by becoming a reviewer" -date: 2016-07-02 -categories: news ---- - -ReScience is slowly gaining momentum and we currently have 4 submissions to -review. If you're interested in helping ReScience and reproducibility, you can -become a reviewer. What you need is a github account, a one line description of -your expertise (see the [Board](http://rescience.github.io/board/) for some -examples) and to [tell us](https://github.com/ReScience/ReScience/issues/27) you're interested such that we can add you to the board. You can also [follow](https://github.com/ReScience/ReScience-submission/subscription) the [submission](https://github.com/ReScience/ReScience-submission) repository and propose your help whenever a submission falls into your expertise domain. - diff --git a/_posts/2016-09-07-Detorakis-post.md b/_posts/2016-09-07-Detorakis-post.md deleted file mode 100644 index fba5a62..0000000 --- a/_posts/2016-09-07-Detorakis-post.md +++ /dev/null @@ -1,9 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Multiple dynamical modes of thalamic relay neurons: rhythmic bursting and intermittent phase-locking" -date: 2016-09-07 -categories: news ---- - -A new replication has just been published in computational neuroscience: *[Re] Multiple dynamical modes of thalamic relay neurons: rhythmic bursting and intermittent phase-locking* - Georgios Detorakis, ReScience, volume 2, issue 1, 2016. diff --git a/_posts/2016-09-07-Detorakis.md b/_posts/2016-09-07-Detorakis.md deleted file mode 100644 index 253b690..0000000 --- a/_posts/2016-09-07-Detorakis.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Multiple dynamical modes of thalamic relay neurons: rhythmic bursting and intermittent phase-locking" -date: 2016-09-07 -categories: neuroscience -author: Georgios Detorakis -volume: 2 -issue: 1 -doi: 10.5281/zenodo.61697 -pdf: https://github.com/ReScience-Archives/Detorakis-2016/raw/master/article/detorakis-2016.pdf -repository: https://github.com/ReScience-Archives/Detorakis-2016.git -review: https://github.com/ReScience/ReScience-submission/pull/17 -zenodo: https://zenodo.org/record/61697 -keywords: Neuroscience, Python, Conductance-based model, Thalamic relay neurons, Intermittent phase-locking, Spindle oscillation, Delta oscillation ---- diff --git a/_posts/2016-10-07-Vitay-post.md b/_posts/2016-10-07-Vitay-post.md deleted file mode 100644 index 81c022f..0000000 --- a/_posts/2016-10-07-Vitay-post.md +++ /dev/null @@ -1,9 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Robust timing and motor patterns by taming chaos in recurrent neural networks" -date: 2016-10-07 -categories: news ---- - -A new replication has just been published in computational neuroscience: *[Re] Robust timing and motor patterns by taming chaos in recurrent neural networks* - Julien Vitay, ReScience, volume 2, issue 1, 2016. diff --git a/_posts/2016-10-07-Vitay.md b/_posts/2016-10-07-Vitay.md deleted file mode 100644 index a140048..0000000 --- a/_posts/2016-10-07-Vitay.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Robust timing and motor patterns by taming chaos in recurrent neural networks" -date: 2016-10-07 -categories: neuroscience -author: Julien Vitay -volume: 2 -issue: 1 -doi: 10.5281/zenodo.159545 -pdf: https://github.com/ReScience-Archives/Vitay-2016/raw/master/article/vitay-2016.pdf -repository: https://github.com/ReScience-Archives/Vitay-2016 -review: https://github.com/ReScience/ReScience-submission/pull/19 -zenodo: https://zenodo.org/record/159545 -keywords: Python, Recurrent neural networks, Reservoir computing, Dynamical systems, Learning Chaos ---- diff --git a/_posts/2016-10-18-Maksimov-Albada-Diesmann-post.md b/_posts/2016-10-18-Maksimov-Albada-Diesmann-post.md deleted file mode 100644 index 45bb7e6..0000000 --- a/_posts/2016-10-18-Maksimov-Albada-Diesmann-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model" -date: 2016-10-18 -categories: news ---- - -A new replication has just been published in computational neuroscience: * -[Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model* - Andrei Maksimov, Sacha J. van Albada and Markus Diesmann, ReScience, volume 2, issue 1, 2016. diff --git a/_posts/2016-10-18-Maksimov-Albada-Diesmann.md b/_posts/2016-10-18-Maksimov-Albada-Diesmann.md deleted file mode 100644 index 973f6a4..0000000 --- a/_posts/2016-10-18-Maksimov-Albada-Diesmann.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model" -date: 2016-10-18 -categories: neuroscience -author: Andrei Maksimov, Sacha J. van Albada and Markus Diesmann -volume: 2 -issue: 1 -doi: 10.5281/zenodo.161526 -pdf: https://github.com/ReScience-Archives/Maksimov-Albada-Diesmann-2016/raw/master/article/maksimov-albada-diesmann-2016.pdf -repository: https://github.com/ReScience-Archives/Maksimov-Albada-Diesmann-2016 -review: https://github.com/ReScience/ReScience-submission/pull/18 -zenodo: https://zenodo.org/record/161526 -keywords: Python, Neuroscience, NEST, Network Modeling, Up-Down Oscillations, Cortex, Membrane Resistance Measurement ---- diff --git a/_posts/2016-10-19-Call-For-Replication.md b/_posts/2016-10-19-Call-For-Replication.md deleted file mode 100644 index 31a7611..0000000 --- a/_posts/2016-10-19-Call-For-Replication.md +++ /dev/null @@ -1,20 +0,0 @@ ---- -layout: post -type: news -title: "Call for replication" -date: 2016-10-19 -categories: news ---- - -It is now possible to suggest an article for a replication. Just -[open a new issue](https://github.com/ReScience/call-for-replication/issues/new) -in the -[call for replication repository](https://github.com/ReScience/call-for-replication) -and give the reference of the original article and possibly the reason you -would like to see this article replicated (please refrain from suggesting your -own work). Note that you're also encouraged to register as a reviewer such that -you can review the replication you've been proposing if someone actually takes -up the challenge. - -If you're looking for some challenge, you can also look at the -[current list of suggestions](https://github.com/ReScience/call-for-replication/issues). diff --git a/_posts/2016-12-12-Le_Masson-Alexandre.md b/_posts/2016-12-12-Le_Masson-Alexandre.md deleted file mode 100644 index dcc8d62..0000000 --- a/_posts/2016-12-12-Le_Masson-Alexandre.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks" -date: 2016-12-09 -categories: neuroscience python -author: Erwan Le Masson & Frédéric Alexandre -volume: 2 -issue: 1 -doi: 10.5281/zenodo.200334 -pdf: https://github.com/ReScience-Archives/Le_Masson-Alexandre-2016/raw/master/article/Le_Masson-Alexandre-2016.pdf -repository: https://github.com/ReScience-Archives/Le_Masson-Alexandre-2016 -review: https://github.com/ReScience/ReScience-submission/pull/21 -zenodo: https://zenodo.org/record/200334 -keywords: neuroscience, deep learning, associative cortex, python ---- diff --git a/_posts/2017-01-20-Shifman-post.md b/_posts/2017-01-20-Shifman-post.md deleted file mode 100644 index bf176c0..0000000 --- a/_posts/2017-01-20-Shifman-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Ionic Current Model of a Hypoglossal Motoneuron" -date: 2017-01-20 -categories: news ---- - -A new replication has just been published in computational neuroscience: * -[Re] Ionic Current Model of a Hypoglossal Motoneuron* - Aaron Shifman, ReScience, volume 3, issue 1, 2017. diff --git a/_posts/2017-01-20-Shifman.md b/_posts/2017-01-20-Shifman.md deleted file mode 100644 index 0324379..0000000 --- a/_posts/2017-01-20-Shifman.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Ionic Current Model of a Hypoglossal Motoneuron" -date: 2017-01-20 -categories: neuroscience -author: Shifman, Aaron -volume: 3 -issue: 1 -doi: 10.5281/zenodo.254145 -pdf: https://github.com/ReScience-Archives/Shifman-2017/raw/master/article/shifman-2017.pdf -repository: https://github.com/ReScience-Archives/Shifman-2017.git -review: https://github.com/ReScience/ReScience-submission/pull/22 -zenodo: https://zenodo.org/record/254145 -keywords: neuroscience, Python, replication ---- diff --git a/_posts/2017-04-05-Henriques-post.md b/_posts/2017-04-05-Henriques-post.md deleted file mode 100644 index d8b7c0e..0000000 --- a/_posts/2017-04-05-Henriques-post.md +++ /dev/null @@ -1,15 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Optimization of a free water elimination two-compartment model for diffusion tensor imaging" -date: 2017-04-05 -categories: news ---- - -A new replication has just been published in computational neuroscience: *[Re] -Optimization of a free water elimination two-compartment model for diffusion -tensor imaging*, Rafael Neto Henriques, Ariel Rokem, Eleftherios Garyfallidis, -Samuel St-Jean, Eric Thomas Peterson, Marta Morgado Correia, ReScience -volume 3, issue 1, article number 2, 2017. - - diff --git a/_posts/2017-04-05-Henriques.md b/_posts/2017-04-05-Henriques.md deleted file mode 100644 index 0821bbc..0000000 --- a/_posts/2017-04-05-Henriques.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Optimization of a free water elimination two-compartment model for diffusion tensor imaging" -date: 2017-04-05 -categories: neuroscience -author: Henriques, Rafael Neto; Rokem, Ariel; Garyfallidis, Eleftherios; St-Jean, Samuel; Peterson, Eric Thomas; Correia, Marta Morgado -volume: 3 -issue: 1 -number: 2 -doi: 10.5281/zenodo.495237 -pdf: https://github.com/ReScience-Archives/Henriques-Rokem-Garyfallidis-St-Jean-Peterson-Correia-2017/raw/master/article/Henriques-Rokem-Garyfallidis-St-Jean-Peterson-Correia-2017.pdf -repository: https://github.com/ReScience-Archives/Henriques-Rokem-Garyfallidis-St-Jean-Peterson-Correia-2017 -review: https://github.com/ReScience/ReScience-submission/pull/26 -zenodo: https://zenodo.org/record/495237 -keywords: Neuroscience, Python, Diffusion-weighted imaging, Diffusion modeling, Diffusion tensor imaging ---- diff --git a/_posts/2017-05-29-Rostami-post.md b/_posts/2017-05-29-Rostami-post.md deleted file mode 100644 index 5f92fcc..0000000 --- a/_posts/2017-05-29-Rostami-post.md +++ /dev/null @@ -1,14 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Spike Synchronization and Rate Modulation Differentially Involved in Motor Cortical Function" -date: 2017-05-29 -categories: news ---- - -A new replication has just been published in computational neuroscience: *[Re] -Spike Synchronization and Rate Modulation Differentially Involved in Motor -Cortical Function*, Vahid Rostami, Junji Ito, Michael Denker, and Sonja Grün, -ReScience, volume 3, issue 1, article number 3, 2017. - - diff --git a/_posts/2017-05-29-Rostami.md b/_posts/2017-05-29-Rostami.md deleted file mode 100644 index ceba5c7..0000000 --- a/_posts/2017-05-29-Rostami.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Spike Synchronization and Rate Modulation Differentially Involved in Motor Cortical Function" -date: 2017-05-29 -categories: neuroscience -author: Vahid Rostami, Junji Ito, Michael Denker, and Sonja Grün -volume: 3 -issue: 1 -number: 3 -doi: 10.5281/zenodo.583814 -pdf: https://github.com/ReScience-Archives/Rostami-Ito-Denker-Gruen-2017/blob/master/article/Rostami-Ito-Denker-Gruen-2017.pdf -repository: https://github.com/ReScience-Archives/Rostami-Ito-Denker-Gruen-2017 -review: https://github.com/ReScience/ReScience-submission/pull/24 -zenodo: https://doi.org/10.5281/zenodo.583814 -keywords: Spike time synchrony, Unitary Events method, Python ---- diff --git a/_posts/2017-06-02-Rougier-post.md b/_posts/2017-06-02-Rougier-post.md deleted file mode 100644 index 61311c2..0000000 --- a/_posts/2017-06-02-Rougier-post.md +++ /dev/null @@ -1,13 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Weighted Voronoi Stippling" -date: 2017-06-02 -categories: news ---- - -A new replication has just been published in signal processing: *[Re] -Weighted Voronoi Stippling*, Nicolas P. Rougier, ReScience volume 3, -issue 1, article number 4, 2017. - - diff --git a/_posts/2017-06-02-Rougier.md b/_posts/2017-06-02-Rougier.md deleted file mode 100644 index 92182fc..0000000 --- a/_posts/2017-06-02-Rougier.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Weighted Voronoi Stippling" -date: 2017-06-02 -categories: signal processing -author: Nicolas P. Rougier -volume: 3 -issue: 1 -number: 4 -doi: 10.5281/zenodo.802285 -pdf: https://github.com/ReScience-Archives/Rougier-2017/blob/master/article/Rougier-2017.pdf -repository: https://github.com/ReScience-Archives/Rougier-2017 -review: https://github.com/ReScience/ReScience-submission/pull/28 -zenodo: https://zenodo.org/record/802285 -keywords: Python, Stippling, Voronoi, Computer Graphics, Blue Noise ---- diff --git a/_posts/2017-07-14-ReScience-arXiv.md b/_posts/2017-07-14-ReScience-arXiv.md deleted file mode 100644 index cddcb9d..0000000 --- a/_posts/2017-07-14-ReScience-arXiv.md +++ /dev/null @@ -1,33 +0,0 @@ ---- -layout: post -type: news -title: "Sustainable computational science: the ReScience initiative" -date: 2017-07-14 -categories: news ---- - -We've just published a white paper on -[the ReScience initiative](https://arxiv.org/abs/1707.04393) on arXiv! - -Computer science offers a large set of tools for prototyping, writing, running, -testing, validating, sharing and reproducing results, however computational -science lags behind. In the best case, authors may provide their source code as -a compressed archive and they may feel confident their research is -reproducible. But this is not exactly true. James Buckheit and David Donoho -proposed more than two decades ago that an article about computational results -is advertising, not scholarship. The actual scholarship is the full software -environment, code, and data that produced the result. This implies new -workflows, in particular in peer-reviews. Existing journals have been slow to -adapt: source codes are rarely requested, hardly ever actually executed to -check that they produce the results advertised in the article. ReScience is a -peer-reviewed journal that targets computational research and encourages the -explicit replication of already published research, promoting new and -open-source implementations in order to ensure that the original research can -be replicated from its description. To achieve this goal, the whole publishing -chain is radically different from other traditional scientific -journals. ReScience resides on GitHub where each new implementation of a -computational study is made available together with comments, explanations, and -software tests. - -Read more at [arxiv.org/abs/1707.04393](https://arxiv.org/abs/1707.04393). - diff --git a/_posts/2017-08-23-Stollmeier-post.md b/_posts/2017-08-23-Stollmeier-post.md deleted file mode 100644 index ffbdcf1..0000000 --- a/_posts/2017-08-23-Stollmeier-post.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -layout: post -type: news -title: "[Re] A simple rule for the evolution of cooperation on graphs and social networks" -date: 2017-08-23 -categories: news ---- - -A new replication has just been published: *[Re] A simple rule for the evolution of cooperation on graphs and social networks*, Frank Stollmeier, ReScience volume 3, issue 1, article number 5, 2017. - - diff --git a/_posts/2017-08-23-Stollmeier.md b/_posts/2017-08-23-Stollmeier.md deleted file mode 100644 index b91e668..0000000 --- a/_posts/2017-08-23-Stollmeier.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] A simple rule for the evolution of cooperation on graphs and social networks" -date: 2017-08-23 -author: Frank Stollmeier -volume: 3 -issue: 1 -number: 5 -doi: 10.5281/zenodo.847732 -pdf: https://github.com/ReScience-Archives/Stollmeier-2017/blob/master/article/Stollmeier-2017.pdf -repository: https://github.com/ReScience-Archives/Stollmeier-2017 -review: https://github.com/ReScience/ReScience-submission/pull/27 -zenodo: https://zenodo.org/record/847732 -keywords: Evolutionary Game Theory, Networks ---- diff --git a/_posts/2017-08-30-Metzner.md b/_posts/2017-08-30-Metzner.md deleted file mode 100644 index a5485b2..0000000 --- a/_posts/2017-08-30-Metzner.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Modeling GABA Alterations in Schizophrenia: A Link Between Impaired Inhibition and Gamma and Beta Auditory Entrainment" -date: 2017-08-30 -categories: neuroscience python -author: Christoph Metzner -volume: 3 -issue: 1 -doi: 10.5281/zenodo.854616 -pdf: https://github.com/ReScience-Archives/Metzner-2017/blob/1.0/article/Metzner-2017.pdf -repository: https://github.com/ReScience-Archives/Metzner-2017/ -review: https://github.com/ReScience/ReScience-submission/pull/30 -zenodo: https://zenodo.org/record/854617 -keywords: Neuroscience, Gamma and Beta Oscillations, Auditory Entrainment, Schizophrenia, Python ---- diff --git a/_posts/2017-09-13-Diem-post.md b/_posts/2017-09-13-Diem-post.md deleted file mode 100644 index 2d02c20..0000000 --- a/_posts/2017-09-13-Diem-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] A bidirectional model for communication in the neurovascular unit" -date: 2017-09-13 -categories: news ---- - -A new replication has just been published in cognitive science: *[Re] A bidirectional model for communication in the neurovascular unit*, Alexandra K. Diem, ReScience volume 3, issue 1, article number 9, 2017. - diff --git a/_posts/2017-09-13-Diem.md b/_posts/2017-09-13-Diem.md deleted file mode 100644 index d44fe98..0000000 --- a/_posts/2017-09-13-Diem.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] A bidirectional model for communication in the neurovascular unit" -date: 2017-09-03 -categories: Life science -author: Alexandra K. Diem -volume: 3 -issue: 1 -number: 9 -doi: 10.5281/zenodo.890901 -pdf: https://github.com/ReScience-Archives/Diem-2017/blob/master/article/Diem-2017.pdf -repository: https://github.com/ReScience-Archives/Diem-2017 -review: https://github.com/ReScience/ReScience-submission/pull/33 -zenodo: https://zenodo.org/record/890901 -keywords: neurovascular modelling, neurovascular unit, chemical signalling, astrocytes, neuroscience ---- diff --git a/_posts/2017-09-13-Stojic-post.md b/_posts/2017-09-13-Stojic-post.md deleted file mode 100644 index 8dc7ada..0000000 --- a/_posts/2017-09-13-Stojic-post.md +++ /dev/null @@ -1,12 +0,0 @@ ---- -layout: post -type: news -title: "[Re] How learning can guide evolution" -date: 2017-09-13 -categories: news ---- - -A new replication has just been published in cognitive science: *[Re] -How learning can guide evolution*, Hrvoje Stojić, ReScience volume 3, -issue 1, article number 8, 2017. - diff --git a/_posts/2017-09-13-Stojic.md b/_posts/2017-09-13-Stojic.md deleted file mode 100644 index 326d9ad..0000000 --- a/_posts/2017-09-13-Stojic.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] How learning can guide evolution" -date: 2017-09-03 -categories: Cognitive science -author: Hrvoje Stojić -volume: 3 -issue: 1 -number: 8 -doi: 10.5281/zenodo.890884 -pdf: https://github.com/ReScience-Archives/Stojic-2017/blob/master/article/Stojic-2017.pdf -repository: https://github.com/ReScience-Archives/Stojic-2017 -review: https://github.com/ReScience/ReScience-submission/pull/36 -zenodo: https://zenodo.org/record/890884 -keywords: R, Evolution, Learning, Baldwin effect ---- diff --git a/_posts/2017-10-06-Detorakis-post.md b/_posts/2017-10-06-Detorakis-post.md deleted file mode 100644 index 5c8c479..0000000 --- a/_posts/2017-10-06-Detorakis-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors" -date: 2017-10-06 -categories: news ---- - -A new replication has just been published in neuroscience: *[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors*, Georgios Detorakis, ReScience volume 3, issue 1, article number 7, 2017. - diff --git a/_posts/2017-10-06-Detorakis.md b/_posts/2017-10-06-Detorakis.md deleted file mode 100644 index 3e516f8..0000000 --- a/_posts/2017-10-06-Detorakis.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors" -date: 2017-10-06 -categories: Neuroscience -author: Georgios Detorakis -volume: 3 -issue: 1 -number: 7 -doi: 10.5281/zenodo.1003214 -pdf: https://github.com/ReScience-Archives/Detorakis-2017/blob/master/article/detorakis-2017.pdf -repository: https://github.com/ReScience-Archives/Detorakis-2017 -review: https://github.com/ReScience/ReScience-submission/pull/35 -zenodo: https://zenodo.org/record/1003214 -keywords: Python, generalized linear integrate-and-fire neuron ---- diff --git a/_posts/2018-05-04-Senden-Schuecker-Hahne-Diesmann-Goebel-post.md b/_posts/2018-05-04-Senden-Schuecker-Hahne-Diesmann-Goebel-post.md deleted file mode 100644 index 9d6014f..0000000 --- a/_posts/2018-05-04-Senden-Schuecker-Hahne-Diesmann-Goebel-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] A neural model of the saccade generator in the reticular formation" -date: 2018-05-04 -categories: news ---- - -A new replication has just been published in neuroscience: *[Re] A neural model of the saccade generator in the reticular formation*, Mario Senden, Jannis Schuecker, Jan Hahne, Markus Diesmann, Rainer Goebel, ReScience volume 4, issue 1, article number 3, 2018. - diff --git a/_posts/2018-05-04-Senden-Schuecker-Hahne-Diesmann-Goebel.md b/_posts/2018-05-04-Senden-Schuecker-Hahne-Diesmann-Goebel.md deleted file mode 100644 index b840db9..0000000 --- a/_posts/2018-05-04-Senden-Schuecker-Hahne-Diesmann-Goebel.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] A neural model of the saccade generator in the reticular formation" -date: 2018-05-04 -categories: Neuroscience -author: Mario Senden, Jannis Schuecker, Jan Hahne, Markus Diesmann, Rainer Goebel -volume: 4 -issue: 1 -number: 3 -doi: 10.5281/zenodo.1241004 -pdf: https://github.com/ReScience-Archives/Senden-Schuecker-Hahne-Diesmann-Goebel-2018/blob/master/article/senden-schuecker-hahne-diesmann-goebel-2018.pdf -repository: https://github.com/ReScience-Archives/Senden-Schuecker-Hahne-Diesmann-Goebel-2018 -review: https://github.com/ReScience/ReScience-submission/pull/46 -zenodo: https://doi.org/10.5281/zenodo.1241004 -keywords: Supercomputing Waveform, relaxation, parallelization, rate models, spiking neural network simulator, stochastic (delay) differential equations ---- diff --git a/_posts/2018-05-07-ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-post.md b/_posts/2018-05-07-ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-post.md deleted file mode 100644 index 90ffea2..0000000 --- a/_posts/2018-05-07-ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model" -date: 2018-05-07 -categories: news ---- - -A new replication has just been published in neuroscience: *[Re] The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model*, Renan O. Shimoura, Nilton L. Kamij1, Rodrigo F.O. Pena, Vinicius L. Cordeiro, Cesar C. Ceballos, Cecilia Romaro, and Antonio C. Roque, ReScience volume 4, issue 1, article number 2, 2018. - diff --git a/_posts/2018-05-07-ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC.md b/_posts/2018-05-07-ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC.md deleted file mode 100644 index a04308e..0000000 --- a/_posts/2018-05-07-ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -layout: post -type: article -title: "[Re] The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model" -date: 2018-05-07 -categories: Neuroscience -author: Renan O. Shimoura, Nilton L. Kamij1, Rodrigo F.O. Pena, Vinicius L. Cordeiro, Cesar C. Ceballos, Cecilia Romaro, and Antonio C. Roque -volume: 4 -issue: 1 -number: 2 -doi: 10.5281/zenodo.1244116 -pdf: https://github.com/ReScience-Archives/ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-2017/blob/master/article/ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-2017.pdf -review: https://github.com/ReScience/ReScience-submission/pull/43 -zenodo: https://doi.org/10.5281/zenodo.1244116 -keywords: cerebral cortex, cortical microcircuit, large-scale models, layered network, specificity of connections ---- diff --git a/_posts/2018-05-14-Case-Stimberg-Girard-post.md b/_posts/2018-05-14-Case-Stimberg-Girard-post.md deleted file mode 100644 index ca70d6a..0000000 --- a/_posts/2018-05-14-Case-Stimberg-Girard-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Non-additive coupling enables propagation of synchronous spiking activity in purely random networks" -date: 2018-05-14 -categories: news ---- - -A new replication has just been published in neuroscience: *[Re] The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model*, Romain Cazé, Marcel Stimberg, and Benoît Girard, ReScience volume 4, issue 1, article number 1, 2018. - diff --git a/_posts/2018-05-14-Case-Stimberg-Girard.md b/_posts/2018-05-14-Case-Stimberg-Girard.md deleted file mode 100644 index 50c2a82..0000000 --- a/_posts/2018-05-14-Case-Stimberg-Girard.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Non-additive coupling enables propagation of synchronous spiking activity in purely random networks" -date: 2018-05-14 -categories: neuroscience python -author: Romain Cazé, Marcel Stimberg, and Benoît Girard -volume: 4 -issue: 1 -number: 1 -doi: 10.5281/zenodo.1246659 -pdf: https://github.com/ReScience-Archives/Caze-Stimberg-Girard-2018/blob/master/article/Caze_2018.pdf -repository: https://github.com/ReScience-Archives/Caze-Stimberg-Girard-2018/ -review: https://github.com/ReScience/ReScience-submission/pull/45 -zenodo: https://zenodo.org/record/1246659 -keywords: Dendrites, non-linearities, network, synfire chain ---- diff --git a/_posts/2018-05-29-Mondeel-Ogundipe-Westerhoff-post.md b/_posts/2018-05-29-Mondeel-Ogundipe-Westerhoff-post.md deleted file mode 100644 index 8f8ff89..0000000 --- a/_posts/2018-05-29-Mondeel-Ogundipe-Westerhoff-post.md +++ /dev/null @@ -1,9 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Predicting metabolic biomarkers of human inborn errors of metabolism" -date: 2018-05-29 -categories: news ---- - -A new replication has just been published in neuroscience: *[Re] Predicting metabolic biomarkers of human inborn errors of metabolism*, Thierry D.G.A. Mondeel, Vivian Ogundipe, and Hans V. Westerhoff, ReScience volume 4, issue 1, article number 4, 2018. diff --git a/_posts/2018-05-29-Mondeel-Ogundipe-Westerhoff.md b/_posts/2018-05-29-Mondeel-Ogundipe-Westerhoff.md deleted file mode 100644 index 1fd55ec..0000000 --- a/_posts/2018-05-29-Mondeel-Ogundipe-Westerhoff.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Predicting metabolic biomarkers of human inborn errors of metabolism" -date: 2018-05-29 -categories: Systems Biology, Computational Biology, Python -author: Thierry D.G.A. Mondeel, Vivian Ogundipe, and Hans V. Westerhoff -volume: 4 -issue: 1 -number: 4 -doi: 10.5281/zenodo.1254629 -pdf: https://github.com/ReScience-Archives/Mondeel-Ogundipe-Westerhoff-2018/blob/master/article/Mondeel_Ogundipe_Westerhoff-2017.pdf -repository: https://github.com/ReScience-Archives/Mondeel-Ogundipe-Westerhoff-2018 -review: https://github.com/ReScience/ReScience-submission/pull/41 -zenodo: https://zenodo.org/record/1254630 -keywords: Flux variability analysis (FVA), inborn errors of metabolism (IEM), metabolic reconstruction ---- diff --git "a/_posts/2018-06-14-Bavard-Th\303\251ro.md" "b/_posts/2018-06-14-Bavard-Th\303\251ro.md" deleted file mode 100644 index 5dbaf6b..0000000 --- "a/_posts/2018-06-14-Bavard-Th\303\251ro.md" +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Adaptive properties of differential learning rates for positive and negative outcomes" -date: 2018-06-14 -categories: neuroscience python -author: Sophie Bavard and Héloïse Théro -volume: 4 -issue: 1 -number: 5 -doi: 10.5281/zenodo.1289889 -pdf: https://github.com/ReScience-Archives/Bavard-Thero-2018/raw/master/article/Bavard-Thero-2018.pdf -repository: https://github.com/ReScience-Archives/Bavard-Thero-2018 -review: https://github.com/ReScience/ReScience-submission/pull/47 -zenodo: https://zenodo.org/record/1289889 -keywords: Reinforcement learning, Q-learning, adaptive learning rates ---- diff --git a/_posts/2018-08-03-Hathway-Goodman-post.md b/_posts/2018-08-03-Hathway-Goodman-post.md deleted file mode 100644 index e60638a..0000000 --- a/_posts/2018-08-03-Hathway-Goodman-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains" -date: 2018-08-03 -categories: news ---- - -A new replication has just been published in neuroscience: *[Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains*, -Pamela Hathway & Dan F. M. Goodman, ReScience volume 4, issue 1, article number 6, 2018. diff --git a/_posts/2018-08-03-Hathway-Goodman.md b/_posts/2018-08-03-Hathway-Goodman.md deleted file mode 100644 index 86dfd9a..0000000 --- a/_posts/2018-08-03-Hathway-Goodman.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains" -date: 2018-08-03 -categories: neuroscience python -author: Pamela Hathway and Dan F. M. Goodman -volume: 4 -issue: 1 -number: 6 -doi: 10.5281/zenodo.1327348 -pdf: https://github.com/ReScience-Archives/Hathway-Goodman-2018/blob/master/article/Hathway-Goodman-2018.pdf -repository: https://github.com/ReScience-Archives/Hathway-Goodman-2018 -review: https://github.com/ReScience/ReScience-submission/pull/51 -zenodo: https://zenodo.org/record/1327348 -keywords: STDP, Spatio-temporal spike pattern, Python, Neuroscience ---- diff --git a/_posts/2018-08-22-Poisot.md b/_posts/2018-08-22-Poisot.md deleted file mode 100644 index a1eaedd..0000000 --- a/_posts/2018-08-22-Poisot.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] On the coexistence of specialists and generalists" -date: 2018-08-22 -categories: Ecology -author: Timothée Poisot -volume: 4 -issue: 1 -number: 7 -doi: 10.5281/zenodo.1402676 -pdf: https://github.com/ReScience-Archives/Poisot-2018/blob/master/article/Poisot-2018.pdf -repository: https://github.com/ReScience-Archives/Poisot-2018 -review: https://github.com/ReScience/ReScience-submission/pull/39 -zenodo: https://zenodo.org/record/1402676 -keywords: community ecology, specialist, generalist, coexistence, discrete time model ---- diff --git a/_posts/2019-03-19-Caron-Lessard-Wu-Poisot-post.md b/_posts/2019-03-19-Caron-Lessard-Wu-Poisot-post.md deleted file mode 100644 index 5b4a9df..0000000 --- a/_posts/2019-03-19-Caron-Lessard-Wu-Poisot-post.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Insect natural enemies as regulating factors" -date: 2019-03-19 -categories: news ---- - -A new replication has just been published in computational ecology: *[Re] Insect natural enemies as regulating factors*, -Dominique Caron, Vincent Lessard, Qile Wu, and Timothée Poisot, ReScience volume 5, issue 1, article number 1, 2019. - diff --git a/_posts/2019-03-19-Caron-Lessard-Wu-Poisot.md b/_posts/2019-03-19-Caron-Lessard-Wu-Poisot.md deleted file mode 100644 index 81ae90b..0000000 --- a/_posts/2019-03-19-Caron-Lessard-Wu-Poisot.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Insect natural enemies as regulating factors" -date: 2019-03-19 -categories: Ecology -author: Dominique Caron, Vincent Lessard, Qile Wu, and Timothée Poisot -volume: 5 -issue: 1 -number: 1 -doi: https://doi.org/10.5281/zenodo.2598793 -pdf: https://github.com/ReScience-Archives/Caron-Lessard-Wu-Poisot-2019/blob/master/article/Caron-Lessard-Wu-Poisot-2019.pdf -repository: https://github.com/ReScience-Archives/Caron-Lessard-Wu-Poisot-2019 -review: https://github.com/ReScience/ReScience-submission/pull/50 -zenodo: https://zenodo.org/record/2598793 -keywords: population dynamics, ecology, stochastic models ---- diff --git a/_posts/2019-03-27-Tennoe-post.md b/_posts/2019-03-27-Tennoe-post.md deleted file mode 100644 index a0d774c..0000000 --- a/_posts/2019-03-27-Tennoe-post.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -layout: post -type: news -title: "[Re] Fast-Activating Voltage- and Calcium-Dependent Potassium (BK) Conductance Promotes Bursting in Pituitary Cells: A Dynamic Clamp Study" -date: 2019-03-27 -categories: news ---- - -A new replication has just been published in computational neuroscience: *[Re] Fast-Activating Voltage- and Calcium-Dependent Potassium (BK) Conductance Promotes Bursting in Pituitary Cells: A Dynamic Clamp Study*, Simen Tennøe, Kjetil Hodne, Trude M. Haug, Finn-Arne Weltzien, Gaute T. Einevoll, & Geir Halnes, ReScience volume 5, -issue 1, article number 2, 2019. diff --git a/_posts/2019-03-27-Tennoe.md b/_posts/2019-03-27-Tennoe.md deleted file mode 100644 index 4ba0dc5..0000000 --- a/_posts/2019-03-27-Tennoe.md +++ /dev/null @@ -1,17 +0,0 @@ ---- -layout: post -type: article -title: "[Re] Fast-Activating Voltage- and Calcium-Dependent Potassium (BK) Conductance Promotes Bursting in Pituitary Cells: A Dynamic Clamp Study" -date: 2019-03-27 -categories: Computational neuroscience -author: Simen Tennøe, Kjetil Hodne, Trude M. Haug, Finn-Arne Weltzien, Gaute T. Einevoll, & Geir Halnes -volume: 5 -issue: 1 -number: 2 -doi: 10.5281/zenodo.2611252 -pdf: https://github.com/ReScience-Archives/Tenn-e-Hodne-Haug-Weltzien-Einevoll-Halnes-2019/blob/master/article/tenn%C3%B8e-hodne-haug-weltzien-einevoll-halnes-2018.pdf -repository: https://github.com/ReScience-Archives/Tenn-e-Hodne-Haug-Weltzien-Einevoll-Halnes-2019 -review: https://github.com/ReScience/ReScience-submission/pull/53 -zenodo: https://zenodo.org/record/2611252 -keywords: Neuroscience, Python, Uncertainty quantification, Pituitary cells ---- diff --git a/_sass/_base.scss b/_sass/_base.scss deleted file mode 100644 index edde0a0..0000000 --- a/_sass/_base.scss +++ /dev/null @@ -1,212 +0,0 @@ -/** - * Reset some basic elements - */ -body, h1, h2, h3, h4, h5, h6, -p, blockquote, pre, hr, -dl, dd, ol, ul, figure { - margin: 0; - padding: 0; -} - - - -/** - * Basic styling - */ -body { - font-family: $base-font-family; - font-size: $base-font-size; - line-height: $base-line-height; - font-weight: 300; 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Agafonov, D., Matthijsse, J., Nonkes, N., and Sande, Z. van de. 2023. [¬Re] A Reproducibility Case Study of “Fairness Guarantees under Demographic Shift.” ReScience C 9, 2, #18.

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Article (PDF):https://zenodo.org/record/8206607/files/article.pdf
Title:[¬Re] A Reproducibility Case Study of “Fairness Guarantees under Demographic Shift”
Author(s):Agafonov, Dennis and Matthijsse, Jelke and Nonkes, Noa and van de Sande, Zjos
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#18
DOI:10.5281/zenodo.8206607
Code URL:https://github.com/noanonkes/fact-guarantee
Code DOI:-
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Review URL:https://openreview.net/forum?id=MMuv-v99Hy
Cite as:Agafonov, D., Matthijsse, J., Nonkes, N., and Sande, Z. van de. 2023. [¬Re] A Reproducibility Case Study of “Fairness Guarantees under Demographic Shift.” ReScience C 9, 2, #18.
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Ahmed, W. and Samuel, S. 2022. [Re] Nondeterminism and Instability in Neural Network Optimization. ReScience C 8, 2, #1.

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Article (PDF):https://zenodo.org/record/6574623/files/article.pdf
Title:[Re] Nondeterminism and Instability in Neural Network Optimization
Author(s):Ahmed, Waqas and Samuel, Sheeba
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#1
DOI:10.5281/zenodo.6574623
Code URL:https://github.com/wi25hoy/MLRC21_Nondeterminism
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Review URL:https://openreview.net/forum?id=BNefkaG73At
Cite as:Ahmed, W. and Samuel, S. 2022. [Re] Nondeterminism and Instability in Neural Network Optimization. ReScience C 8, 2, #1.
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Aillet, A. and Sondén, S. 2023. [Re] Variational Neural Cellular Automata. ReScience C 9, 2, #31.

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Article (PDF):https://zenodo.org/record/8173729/files/article.pdf
Title:[Re] Variational Neural Cellular Automata
Author(s):Aillet, Albert and Sondén, Simon
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#31
DOI:10.5281/zenodo.8173729
Code URL:https://github.com/albertaillet/vnca
Code DOI:10.5281/zenodo.7927205
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Review URL:https://openreview.net/forum?id=d7-ns6SZqp
Cite as:Aillet, A. and Sondén, S. 2023. [Re] Variational Neural Cellular Automata. ReScience C 9, 2, #31.
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Alacchi, G., Lam, G., and Perreault-Lafleur, C. 2020. [Re] Unsupervised Representation Learning in Atari. ReScience C 6, 2, #1.

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Article (PDF):https://zenodo.org/record/3818625/files/article.pdf
Title:[Re] Unsupervised Representation Learning in Atari
Author(s):Alacchi, Gabriel and Lam, Guillaume and Perreault-Lafleur, Carl
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#1
DOI:10.5281/zenodo.3818625
Code URL:https://github.com/GabrielAlacchi/atari-ari-extensions
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Review URL:https://openreview.net/forum?id=GAY8Xw9Qzs
Cite as:Alacchi, G., Lam, G., and Perreault-Lafleur, C. 2020. [Re] Unsupervised Representation Learning in Atari. ReScience C 6, 2, #1.
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Albanis, G., Zioulis, N., Chatzitofis, A., Dimou, A., Zarpalas, D., and Daras, P. 2021. [Re] On end-to-end 6DoF object pose estimation and robustness to object scale. ReScience C 7, 2, #2.

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Article (PDF):https://zenodo.org/record/4833219/files/article.pdf
Title:[Re] On end-to-end 6DoF object pose estimation and robustness to object scale
Author(s):Albanis, Georgios and Zioulis, Nikolaos and Chatzitofis, Anargyros and Dimou, Anastasios and Zarpalas, Dimitrios and Daras, Petros
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#2
DOI:10.5281/zenodo.4833219
Code URL:https://github.com/tzole1155/EndToEndObjectPose
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Data DOI:10.5281/zenodo.3994337
Review URL:https://openreview.net/forum?id=PCpGvUrwfQB
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Alexander, S., Ildus, S., and Evgeniy, S. 2023. [Re] "Towards Understanding Grokking". ReScience C 9, 2, #42.

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Title:[Re] "Towards Understanding Grokking"
Author(s):Alexander, Shabalin and Ildus, Sadrtdinov and Evgeniy, Shabalin
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#42
DOI:10.5281/zenodo.8173755
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Data URL:http://yann.lecun.com/exdb/mnist/
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Cite as:Alexander, S., Ildus, S., and Evgeniy, S. 2023. [Re] "Towards Understanding Grokking". ReScience C 9, 2, #42.
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Allard, T., Béziaud, L., and Gambs, S. 2023. [ Re]Simulating socioeconomic-based affirmative action. ReScience C 9, 1, #2.

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Title:[ Re]Simulating socioeconomic-based affirmative action
Author(s):Allard, Tristan and Béziaud, Louis and Gambs, Sébastien
Journal:ReScience C
Year:2023
Month:nov
Volume:9
Issue:1
Number:#2
DOI:10.5281/zenodo.10255347
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Cite as:Allard, T., Béziaud, L., and Gambs, S. 2023. [ Re]Simulating socioeconomic-based affirmative action. ReScience C 9, 1, #2.
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Ankit, A., Ambekar, S., Varadharajan, B., and Alence, M. 2022. [Re] Counterfactual Generative Networks. ReScience C 8, 2, #2.

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Article (PDF):https://zenodo.org/record/6574625/files/article.pdf
Title:[Re] Counterfactual Generative Networks
Author(s):Ankit, Ankit and Ambekar, Sameer and Varadharajan, Baradwaj and Alence, Mark
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#2
DOI:10.5281/zenodo.6574625
Code URL:https://github.com/ambekarsameer96/FACT_AI/
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Review URL:https://openreview.net/forum?id=BSHg22G7n0F
Cite as:Ankit, A., Ambekar, S., Varadharajan, B., and Alence, M. 2022. [Re] Counterfactual Generative Networks. ReScience C 8, 2, #2.
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Antequera, P., Gonzalez, E., Grasa, M., and Raaphorst, M. van. 2023. [Re] RELIC: Reproducibility and Extension on LIC metric in quantifying bias in captioning models. ReScience C 9, 2, #36.

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Title:[Re] RELIC: Reproducibility and Extension on LIC metric in quantifying bias in captioning models
Author(s):Antequera, Paula and Gonzalez, Egoitz and Grasa, Marta and van Raaphorst, Martijn
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#36
DOI:10.5281/zenodo.8173741
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Cite as:Antequera, P., Gonzalez, E., Grasa, M., and Raaphorst, M. van. 2023. [Re] RELIC: Reproducibility and Extension on LIC metric in quantifying bias in captioning models. ReScience C 9, 2, #36.
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Arvind, M. and Mama, M. 2021. [Re] Neural Networks Fail to Learn Periodic Functions and How to Fix It. ReScience C 7, 2, #3.

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Title:[Re] Neural Networks Fail to Learn Periodic Functions and How to Fix It
Author(s):Arvind, Mayur and Mama, Mustansir
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#3
DOI:10.5281/zenodo.4833389
Code URL:https://github.com/mayurak47/Reproducibility_Challenge
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Cite as:Arvind, M. and Mama, M. 2021. [Re] Neural Networks Fail to Learn Periodic Functions and How to Fix It. ReScience C 7, 2, #3.
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Ashok, A. and Aekula, H. 2022. [Re] Does Self-Supervision Always Improve Few-Shot Learning? ReScience C 8, 2, #3.

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Title:[Re] Does Self-Supervision Always Improve Few-Shot Learning?
Author(s):Ashok, Arjun and Aekula, Haswanth
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#3
DOI:10.5281/zenodo.6574629
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Cite as:Ashok, A. and Aekula, H. 2022. [Re] Does Self-Supervision Always Improve Few-Shot Learning? ReScience C 8, 2, #3.
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Athanasiadis, I., Moschovis, G., and Tuoma, A. 2022. [Re] Weakly-Supervised Semantic Segmentation via Transformer Explainability. ReScience C 8, 2, #4.

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Article (PDF):https://zenodo.org/record/6574631/files/article.pdf
Title:[Re] Weakly-Supervised Semantic Segmentation via Transformer Explainability
Author(s):Athanasiadis, Ioannis and Moschovis, Georgios and Tuoma, Alexander
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#4
DOI:10.5281/zenodo.6574631
Code URL:https://github.com/athaioan/ViT_Affinity_Reproducibility_Challenge
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Data URL:-
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Review URL:https://openreview.net/forum?id=rcEDhGX3AY
Cite as:Athanasiadis, I., Moschovis, G., and Tuoma, A. 2022. [Re] Weakly-Supervised Semantic Segmentation via Transformer Explainability. ReScience C 8, 2, #4.
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Bagad, P., Hilders, P., Maas, J., and Goede, D. de. 2022. [Re] Reproducibility Study of “Counterfactual Generative Networks.” ReScience C 8, 2, #5.

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Article (PDF):https://zenodo.org/record/6574635/files/article.pdf
Title:[Re] Reproducibility Study of “Counterfactual Generative Networks”
Author(s):Bagad, Piyush and Hilders, Paul and Maas, Jesse and de Goede, Danilo
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#5
DOI:10.5281/zenodo.6574635
Code URL:https://github.com/danilodegoede/fact-team3/
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Data URL:-
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Review URL:https://openreview.net/forum?id=HNlzT3G720t
Cite as:Bagad, P., Hilders, P., Maas, J., and Goede, D. de. 2022. [Re] Reproducibility Study of “Counterfactual Generative Networks.” ReScience C 8, 2, #5.
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Balsells Rodas, C., Canal Anton, O., and Taschin, F. 2021. [Re] Hamiltonian Generative Networks. ReScience C 7, 2, #18.

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Title:[Re] Hamiltonian Generative Networks
Author(s):Balsells Rodas, Carles and Canal Anton, Oleguer and Taschin, Federico
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#18
DOI:10.5281/zenodo.4835278
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Review URL:https://openreview.net/forum?id=Zszk4rXgesL
Cite as:Balsells Rodas, C., Canal Anton, O., and Taschin, F. 2021. [Re] Hamiltonian Generative Networks. ReScience C 7, 2, #18.
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Baratov, F., Yüksel, G., Petcu, D., and Bakker, J. 2023. [Re] Reproducibility Study of "Quantifying Societal Bias Amplification in Image Captioning". ReScience C 9, 2, #26.

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Article (PDF):https://zenodo.org/record/8173715/files/article.pdf
Title:[Re] Reproducibility Study of "Quantifying Societal Bias Amplification in Image Captioning"
Author(s):Baratov, Farrukh and Yüksel, Göksenin and Petcu, Darie and Bakker, Jan
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#26
DOI:10.5281/zenodo.8173715
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Review URL:https://openreview.net/forum?id=eJmQJT0Dtt
Cite as:Baratov, F., Yüksel, G., Petcu, D., and Bakker, J. 2023. [Re] Reproducibility Study of "Quantifying Societal Bias Amplification in Image Captioning". ReScience C 9, 2, #26.
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Bardi, F., von Baussnern, S., and Gjiriti, E. 2019. [Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #3.

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Title:[Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019
Author(s):Bardi, Francesco and von Baussnern, Samuel and Gjiriti, Emiljano
Journal:ReScience C
Year:2019
Month:may
Volume:5
Issue:2
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DOI:10.5281/zenodo.3162890
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Cite as:Bardi, F., von Baussnern, S., and Gjiriti, E. 2019. [Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #3.
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Barnett, A. 2020. [Rp] Estimating trends and seasonality in coronary heart disease. ReScience C 6, 1, #18.

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Title:[Rp] Estimating trends and seasonality in coronary heart disease
Author(s):Barnett, Adrian
Journal:ReScience C
Year:2020
Month:nov
Volume:6
Issue:1
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/21
Cite as:Barnett, A. 2020. [Rp] Estimating trends and seasonality in coronary heart disease. ReScience C 6, 1, #18.
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Belitsky, M., Laitenberger, F., Sheremet, D., and Belkacemi, N. 2025. [Re] Learning Fair Graph Representations via Automated Data Augmentations. ReScience C 10, 1, #6.

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Title:[Re] Learning Fair Graph Representations via Automated Data Augmentations
Author(s):Belitsky, Max and Laitenberger, Filipe and Sheremet, Denys and Belkacemi, Nordin
Journal:ReScience C
Year:2025
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Volume:10
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Review URL:https://openreview.net/forum?id=9OlU865dAF
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Benmerzoug, A. and Benito Delgado, M. de. 2023. [Re] If you like Shapley, then you’ll love the core. ReScience C 9, 2, #32.

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Title:[Re] If you like Shapley, then you’ll love the core
Author(s):Benmerzoug, Anes and de Benito Delgado, Miguel
Journal:ReScience C
Year:2023
Month:jul
Volume:9
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DOI:10.5281/zenodo.8173733
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Code DOI:-
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Review URL:https://openreview.net/forum?id=vWzZQAahuW
Cite as:Benmerzoug, A. and Benito Delgado, M. de. 2023. [Re] If you like Shapley, then you’ll love the core. ReScience C 9, 2, #32.
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Bikker, D., Kleuver, G. de, Hu, W., and Veenman, B. 2023. [¬Re] Reproducibility study of ‘Proto2Proto: Can you recognize the car, the way I do?’ ReScience C 9, 2, #22.

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Article (PDF):https://zenodo.org/record/8173705/files/article.pdf
Title:[¬Re] Reproducibility study of ‘Proto2Proto: Can you recognize the car, the way I do?’
Author(s):Bikker, David and de Kleuver, Gerson and Hu, Wenhua and Veenman, Bram
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#22
DOI:10.5281/zenodo.8173705
Code URL:https://github.com/gersondekleuver/Fact
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Review URL:https://openreview.net/forum?id=a_9YF58u61
Cite as:Bikker, D., Kleuver, G. de, Hu, W., and Veenman, B. 2023. [¬Re] Reproducibility study of ‘Proto2Proto: Can you recognize the car, the way I do?’ ReScience C 9, 2, #22.
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Mahmoudian, S. 2020. [Re] Measures for investigating the contextual modulation of information transmission. ReScience C 6, 3, #2.

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Article (PDF):https://zenodo.org/record/3885793/files/Reproduction_of_Smyth_et_al__1996.pdf
Title:[Re] Measures for investigating the contextual modulation of information transmission
Author(s):Mahmoudian, Sepehr
Journal:ReScience C
Year:2020
Month:jun
Volume:6
Issue:3
Number:#2
DOI:10.5281/zenodo.3885793
Code URL:https://github.com/sepehrmn/mahmoudian-2020-rescience
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/29
Cite as:Mahmoudian, S. 2020. [Re] Measures for investigating the contextual modulation of information transmission. ReScience C 6, 3, #2.
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Bock, P. and Alexandre, F. 2019. [Re] The Wisconsin Card Sorting Test: Theoretical analysis and modeling in a neuronal network. ReScience C 5, 3, #3.

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Article (PDF):https://zenodo.org/record/3545905/files/ReScience_Dehaene.pdf +
Title:[Re] The Wisconsin Card Sorting Test: Theoretical analysis and modeling in a neuronal network
Author(s):Bock, Pauline and Alexandre, Frédéric
Journal:ReScience C
Year:2019
Month:may
Volume:5
Issue:3
Number:#3
DOI:10.5281/zenodo.3545905
Code URL:https://github.com/PaulineBock/WCSTDehaeneChangeux
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/7
Cite as:Bock, P. and Alexandre, F. 2019. [Re] The Wisconsin Card Sorting Test: Theoretical analysis and modeling in a neuronal network. ReScience C 5, 3, #3.
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Boer, S. de, Cosma, R.A., Knobel, L., Koishekenov, Y., and Shaffrey, B. 2022. [Re] Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling. ReScience C 8, 2, #6.

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Article (PDF):https://zenodo.org/record/6574637/files/article.pdf
Title:[Re] Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling
Author(s):de Boer, Sarah and Cosma, Radu Alexandru and Knobel, Lukas and Koishekenov, Yeskendir and Shaffrey, Benjamin
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#6
DOI:10.5281/zenodo.6574637
Code URL:https://github.com/reproducibilityaccount/reproducing-ridesharing
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Cite as:Boer, S. de, Cosma, R.A., Knobel, L., Koishekenov, Y., and Shaffrey, B. 2022. [Re] Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling. ReScience C 8, 2, #6.
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Boersch-Supan, P.H. 2021. [Re] Modeling Insect Phenology Using Ordinal Regression and Continuation Ratio Models. ReScience C 7, 1, #5.

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Title:[Re] Modeling Insect Phenology Using Ordinal Regression and Continuation Ratio Models
Author(s):Boersch-Supan, Philipp H.
Journal:ReScience C
Year:2021
Month:jun
Volume:7
Issue:1
Number:#5
DOI:10.5281/zenodo.5006005
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Cite as:Boersch-Supan, P.H. 2021. [Re] Modeling Insect Phenology Using Ordinal Regression and Continuation Ratio Models. ReScience C 7, 1, #5.
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Boettiger, C. 2020. [Rp] Fluctuation domains in adaptive evolution. ReScience C 6, 1, #15.

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Title:[Rp] Fluctuation domains in adaptive evolution
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Journal:ReScience C
Year:2020
Month:sep
Volume:6
Issue:1
Number:#15
DOI:10.5281/zenodo.4081202
Code URL:https://github.com/cboettig/fluctationDomains
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Review URL:https://github.com/ReScience/submissions/issues/16
Cite as:Boettiger, C. 2020. [Rp] Fluctuation domains in adaptive evolution. ReScience C 6, 1, #15.
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Bond-Lamberty, B. 2021. [Re] Drivers of evapotranspiration from boreal wildfires. ReScience C 6, 1, #21.

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Title:[Re] Drivers of evapotranspiration from boreal wildfires
Author(s):Bond-Lamberty, Ben
Journal:ReScience C
Year:2021
Month:mar
Volume:6
Issue:1
Number:#21
DOI:10.5281/zenodo.4617894
Code URL:https://github.com/bpbond/ten-years-paper33
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Data URL:https://github.com/bpbond/ten-years-paper33/blob/master/ET.csv
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Review URL:https://github.com/ReScience/submissions/issues/40
Cite as:Bond-Lamberty, B. 2021. [Re] Drivers of evapotranspiration from boreal wildfires. ReScience C 6, 1, #21.
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Boraud, T. and Strock, A. 2021. [Re] A Neurodynamical Model for Working Memory. ReScience C 7, 1, #1.

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Title:[Re] A Neurodynamical Model for Working Memory
Author(s):Boraud, Theophile and Strock, Anthony
Journal:ReScience C
Year:2021
Month:apr
Volume:7
Issue:1
Number:#1
DOI:10.5281/zenodo.4655870
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/8
Cite as:Boraud, T. and Strock, A. 2021. [Re] A Neurodynamical Model for Working Memory. ReScience C 7, 1, #1.
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Bosch, E., Ettes, R., Korporaal, D., and Meer, G. van. 2022. [Re] Replication study of ’Explaining in Style: Training a GAN to explain a classifier in StyleSpace.’ None 8, 2, #21.

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Article (PDF):https://zenodo.org/record/6574667/files/article.pdf
Title:[Re] Replication study of ’Explaining in Style: Training a GAN to explain a classifier in StyleSpace’
Author(s):Bosch, Evaline and Ettes, Rutger and Korporaal, Daan and van Meer, Gijs
Journal:None
Year:2022
Month:may
Volume:8
Issue:2
Number:#21
DOI:10.5281/zenodo.6574667
Code URL:https://github.com/Gijsvanmeer/FACTinAI
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Data URL:-
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Review URL:https://openreview.net/forum?id=BtIz0nz7hRY
Cite as:Bosch, E., Ettes, R., Korporaal, D., and Meer, G. van. 2022. [Re] Replication study of ’Explaining in Style: Training a GAN to explain a classifier in StyleSpace.’ None 8, 2, #21.
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Bose, P., Pandey, C.S., and Fund, F. 2023. [Re] Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate Speech Classification. ReScience C 9, 2, #35.

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Article (PDF):https://zenodo.org/record/8173739/files/article.pdf
Title:[Re] Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate Speech Classification
Author(s):Bose, Priyanka and Pandey, Chandra Shekhar and Fund, Fraida
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#35
DOI:10.5281/zenodo.8173739
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Review URL:https://openreview.net/forum?id=MjZVx7a0KX-
Cite as:Bose, P., Pandey, C.S., and Fund, F. 2023. [Re] Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate Speech Classification. ReScience C 9, 2, #35.
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Bouwman, P., Li, Y., Weerd, R. van der, and Verhoef, F. 2021. [Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency? ReScience C 7, 2, #22.

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Article (PDF):https://zenodo.org/record/4835592/files/article.pdf
Title:[Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency?
Author(s):Bouwman, Pieter and Li, Yun and van der Weerd, Rogier and Verhoef, Frank
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#22
DOI:10.5281/zenodo.4835592
Code URL:https://github.com/MotherOfUnicorns/FACT_AI_project
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Data URL:-
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Review URL:https://openreview.net/forum?id=lE0wqKGROKa
Cite as:Bouwman, P., Li, Y., Weerd, R. van der, and Verhoef, F. 2021. [Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency? ReScience C 7, 2, #22.
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Brivio, M. and Çöltekin, Ç. 2022. [¬Re] Hate Speech Detection based on Sentiment Knowledge Sharing. ReScience C 8, 2, #7.

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Article (PDF):https://zenodo.org/record/6574639/files/article.pdf
Title:[¬Re] Hate Speech Detection based on Sentiment Knowledge Sharing
Author(s):Brivio, Matteo and Çöltekin, Çağrı
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#7
DOI:10.5281/zenodo.6574639
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Cite as:Brivio, M. and Çöltekin, Ç. 2022. [¬Re] Hate Speech Detection based on Sentiment Knowledge Sharing. ReScience C 8, 2, #7.
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Brivio, M. and Çöltekin, Ç. 2023. [Re] Exploring the Representation of Word Meanings in Context. ReScience C 9, 2, #5.

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Article (PDF):https://zenodo.org/record/8173658/files/article.pdf
Title:[Re] Exploring the Representation of Word Meanings in Context
Author(s):Brivio, Matteo and Çöltekin, Çağrı
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#5
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Review URL:https://openreview.net/forum?id=Od5dD58libt
Cite as:Brivio, M. and Çöltekin, Ç. 2023. [Re] Exploring the Representation of Word Meanings in Context. ReScience C 9, 2, #5.
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Broman, K.W. 2020. [Rp] Reproducibility report: Identifying essential genes by mutagenesis. ReScience C 6, 1, #12.

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Title:[Rp] Reproducibility report: Identifying essential genes by mutagenesis
Author(s):Broman, Karl W.
Journal:ReScience C
Year:2020
Month:jul
Volume:6
Issue:1
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DOI:10.5281/zenodo.3959516
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Cite as:Broman, K.W. 2020. [Rp] Reproducibility report: Identifying essential genes by mutagenesis. ReScience C 6, 1, #12.
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Brückner, L. and Nioche, A. 2020. [Re] Faster Teaching via POMDP Planning. ReScience C 6, 3, #7.

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Article (PDF):https://zenodo.org/record/4242943/files/article.pdf
Title:[Re] Faster Teaching via POMDP Planning
Author(s):Brückner, Lukas and Nioche, Aurélien
Journal:ReScience C
Year:2020
Month:nov
Volume:6
Issue:3
Number:#7
DOI:10.5281/zenodo.4242943
Code URL:https://github.com/luksurious/faster-teaching
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/44
Cite as:Brückner, L. and Nioche, A. 2020. [Re] Faster Teaching via POMDP Planning. ReScience C 6, 3, #7.
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Buchner, V.L., Schutte, P.O.O., Allal, Y.B., and Ahadi, H. 2023. [Re] Fairness Guarantees under Demographic Shift. ReScience C 9, 2, #13.

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Article (PDF):https://zenodo.org/record/8173680/files/article.pdf
Title:[Re] Fairness Guarantees under Demographic Shift
Author(s):Buchner, Valentin Leonhard and Schutte, Philip Onno Olivier and Allal, Yassin Ben and Ahadi, Hamed
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#13
DOI:10.5281/zenodo.8173680
Code URL:https://github.com/YasBenAll/fact-ai-project
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Cite as:Buchner, V.L., Schutte, P.O.O., Allal, Y.B., and Ahadi, H. 2023. [Re] Fairness Guarantees under Demographic Shift. ReScience C 9, 2, #13.
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Buis, E., Dijkstra, S., and Heijermans, B. 2023. [Re] Reproducibility study of “Explaining Deep Convolutional Neural Networks via Latent Visual-Semantic Filter Attention.” ReScience C 9, 2, #25.

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Article (PDF):https://zenodo.org/record/8173713/files/article.pdf
Title:[Re] Reproducibility study of “Explaining Deep Convolutional Neural Networks via Latent Visual-Semantic Filter Attention”
Author(s):Buis, Erik and Dijkstra, Sebastiaan and Heijermans, Bram
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#25
DOI:10.5281/zenodo.8173713
Code URL:https://github.com/ErikBuis/FACT2023
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Review URL:https://openreview.net/forum?id=nsrHznwHhl
Cite as:Buis, E., Dijkstra, S., and Heijermans, B. 2023. [Re] Reproducibility study of “Explaining Deep Convolutional Neural Networks via Latent Visual-Semantic Filter Attention.” ReScience C 9, 2, #25.
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Burger, M., Burg, K. ter, Titarsolej, S., and Khan, S.J. 2022. [Re] Reproducibility Study - SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition. ReScience C 8, 2, #8.

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Article (PDF):https://zenodo.org/record/6574641/files/article.pdf
Title:[Re] Reproducibility Study - SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition
Author(s):Burger, Maarten and ter Burg, Kaya and Titarsolej, Sam and Khan, Selina Jasmin
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#8
DOI:10.5281/zenodo.6574641
Code URL:https://github.com/kayatb/reproduce_SCOUTER
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Review URL:https://openreview.net/forum?id=HZNlq3fmhRF
Cite as:Burger, M., Burg, K. ter, Titarsolej, S., and Khan, S.J. 2022. [Re] Reproducibility Study - SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition. ReScience C 8, 2, #8.
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Buvanesh, A. and Panwar, M. 2022. [Re] AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients. ReScience C 8, 2, #9.

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Article (PDF):https://zenodo.org/record/6574643/files/article.pdf
Title:[Re] AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
Author(s):Buvanesh, Anirudh and Panwar, Madhur
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#9
DOI:10.5281/zenodo.6574643
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Data URL:-
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Review URL:https://openreview.net/forum?id=B9gDnMmn0t
Cite as:Buvanesh, A. and Panwar, M. 2022. [Re] AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients. ReScience C 8, 2, #9.
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Camara, P., Kloos, M., Kyrmanidi, V., Kluska, A., Terlou, R., and Krause, L. 2023. [Re] DialSummEval - Evaluation of automatic summarization evaluation metrics. ReScience C 9, 2, #14.

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Article (PDF):https://zenodo.org/record/8173682/files/article.pdf
Title:[Re] DialSummEval - Evaluation of automatic summarization evaluation metrics
Author(s):Camara, Patrick and Kloos, Mojca and Kyrmanidi, Vasiliki and Kluska, Agnieszka and Terlou, Rorick and Krause, Lea
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#14
DOI:10.5281/zenodo.8173682
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Cite as:Camara, P., Kloos, M., Kyrmanidi, V., Kluska, A., Terlou, R., and Krause, L. 2023. [Re] DialSummEval - Evaluation of automatic summarization evaluation metrics. ReScience C 9, 2, #14.
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Carvalho, T.T.A., Domingos, L.B., Shimoura, R.O., et al. 2021. [Re] Context-Dependent Encoding of Fear and Extinction Memories in a Large-Scale Network Model of the Basal Amygdala. ReScience C 7, 1, #9.

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Article (PDF):https://zenodo.org/record/5657320/files/article.pdf
Title:[Re] Context-Dependent Encoding of Fear and Extinction Memories in a Large-Scale Network Model of the Basal Amygdala
Author(s):Carvalho, Tawan T. A. and Domingos, Luana B. and Shimoura, Renan O. and Kamiji, Nilton L. and Cordeiro, Vinicius L. and Copelli, Mauro and Roque, Antonio C.
Journal:ReScience C
Year:2021
Month:sep
Volume:7
Issue:1
Number:#9
DOI:10.5281/zenodo.5657320
Code URL:https://github.com/tawantayron/RE-Fear-and-extinction-in-a-BA-net-model
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/49
Cite as:Carvalho, T.T.A., Domingos, L.B., Shimoura, R.O., et al. 2021. [Re] Context-Dependent Encoding of Fear and Extinction Memories in a Large-Scale Network Model of the Basal Amygdala. ReScience C 7, 1, #9.
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Casco-Rodriguez, J., Kemere, C., and Baraniuk, R.G. 2025. [Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models. ReScience C 10, 1, #3.

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Article (PDF):https://zenodo.org/record/15172014/files/article.pdf
Title:[Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models
Author(s):Casco-Rodriguez, Josue and Kemere, Caleb and Baraniuk, Richard G.
Journal:ReScience C
Year:2025
Month:apr
Volume:10
Issue:1
Number:#3
DOI:10.5281/zenodo.15172014
Code URL:https://github.com/Josuelmet/Discriminative-Kalman-Filter-4.5-Python
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Data URL:https://portal.nersc.gov/project/crcns/download/dream/data_sets/Flint_2012
Data DOI:10.1088/1741-2560/9/4/046006
Review URL:https://github.com/ReScience/submissions/issues/74
Cite as:Casco-Rodriguez, J., Kemere, C., and Baraniuk, R.G. 2025. [Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models. ReScience C 10, 1, #3.
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Caspar, L. and Moore, R.K. 2025. [Re] An anatomically constrained neural network model of fear conditioning. ReScience C 10, 5, #18.

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Article (PDF):https://zenodo.org/record/11077385/files/article.pdf
Title:[Re] An anatomically constrained neural network model of fear conditioning
Author(s):Caspar, Luc and Moore, Roger K.
Journal:ReScience C
Year:2025
Month:apr
Volume:10
Issue:5
Number:#18
DOI:10.5281_zenodo.11077385
Code URL:https://gitlab.com/davinellulinvega/armony
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Data URL:-
Data DOI:https://doi.org/10.5281/zenodo.5550570
Review URL:https://github.com/ReScience/submissions/issues/60
Cite as:Caspar, L. and Moore, R.K. 2025. [Re] An anatomically constrained neural network model of fear conditioning. ReScience C 10, 5, #18.
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Charisoudis, A., Huth, S.E. von, and Jansson, E. 2023. [Re] Masked Autoencoders Are Small Scale Vision Learners: A Reproduction Under Resource Constraints. ReScience C 9, 2, #40.

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Title:[Re] Masked Autoencoders Are Small Scale Vision Learners: A Reproduction Under Resource Constraints
Author(s):Charisoudis, Athanasios and von Huth, Simon Ekman and Jansson, Emil
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#40
DOI:10.5281/zenodo.8173751
Code URL:https://github.com/MLReproHub/SMAE
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Data URL:-
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Review URL:https://openreview.net/forum?id=KXfjZPL5pqr
Cite as:Charisoudis, A., Huth, S.E. von, and Jansson, E. 2023. [Re] Masked Autoencoders Are Small Scale Vision Learners: A Reproduction Under Resource Constraints. ReScience C 9, 2, #40.
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Chen, A., Matsumoto, S., and Varma, R.S. 2022. [Re] Projection-based Algorithm for Updating the TruncatedSVD of Evolving Matrices. ReScience C 8, 2, #25.

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Article (PDF):https://zenodo.org/record/6574675/files/article.pdf
Title:[Re] Projection-based Algorithm for Updating the TruncatedSVD of Evolving Matrices
Author(s):Chen, Andy and Matsumoto, Shion and Varma, Rohan Sinha
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#25
DOI:10.5281/zenodo.6574675
Code URL:https://github.com/andyzfchen/truncatedSVD
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Data URL:-
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Review URL:https://openreview.net/forum?id=HN2xWpMQ30K
Cite as:Chen, A., Matsumoto, S., and Varma, R.S. 2022. [Re] Projection-based Algorithm for Updating the TruncatedSVD of Evolving Matrices. ReScience C 8, 2, #25.
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Cordaro, D., Cox, S., Ren, Y., and Yu, T. 2023. [¬Re] G-Mixup: Graph Data Augmentation for Graph Classification. ReScience C 9, 2, #34.

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Article (PDF):https://zenodo.org/record/8173737/files/article.pdf
Title:[¬Re] G-Mixup: Graph Data Augmentation for Graph Classification
Author(s):Cordaro, Dylan and Cox, Shelby and Ren, Yiman and Yu, Teresa
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#34
DOI:10.5281/zenodo.8173737
Code URL:https://github.com/shelbycox/EECS-553-GMixup-Reproduction
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Data URL:-
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Review URL:https://openreview.net/forum?id=T54wy0ahGLG¬eId=pvukxfvJGX
Cite as:Cordaro, D., Cox, S., Ren, Y., and Yu, T. 2023. [¬Re] G-Mixup: Graph Data Augmentation for Graph Classification. ReScience C 9, 2, #34.
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Courtès, L. 2020. [Re] Storage Tradeoffs in a Collaborative Backup Service for Mobile Devices. ReScience C 6, 1, #6.

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Title:[Re] Storage Tradeoffs in a Collaborative Backup Service for Mobile Devices
Author(s):Courtès, Ludovic
Journal:ReScience C
Year:2020
Month:jun
Volume:6
Issue:1
Number:#6
DOI:10.5281/zenodo.3886739
Code URL:https://gitlab.inria.fr/lcourtes-phd/edcc-2006-redone
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/32
Cite as:Courtès, L. 2020. [Re] Storage Tradeoffs in a Collaborative Backup Service for Mobile Devices. ReScience C 6, 1, #6.
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Dansereau, G., Banville, F., Basque, E., MacDonald, A., and Poisot, T. 2020. [Re] Chaos in a Three-Species Food Chain. ReScience C 6, 3, #5.

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Article (PDF):https://zenodo.org/record/4022518/files/article.pdf
Title:[Re] Chaos in a Three-Species Food Chain
Author(s):Dansereau, Gabriel and Banville, Francis and Basque, Elodie and MacDonald, Andrew and Poisot, Timothée
Journal:ReScience C
Year:2020
Month:sep
Volume:6
Issue:3
Number:#5
DOI:10.5281/zenodo.4022518
Code URL:https://github.com/BIO6032/2019_replication_HastingsPowell_1991/
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Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/15
Cite as:Dansereau, G., Banville, F., Basque, E., MacDonald, A., and Poisot, T. 2020. [Re] Chaos in a Three-Species Food Chain. ReScience C 6, 3, #5.
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Dasu, V.A. and T.K., M.M. 2022. [Re] GANSpace: Discovering Interpretable GAN Controls. ReScience C 8, 2, #10.

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Article (PDF):https://zenodo.org/record/6574645/files/article.pdf
Title:[Re] GANSpace: Discovering Interpretable GAN Controls
Author(s):Dasu, Vishnu Asutosh and T.K., Midhush Manohar
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#10
DOI:10.5281/zenodo.6574645
Code URL:https://github.com/midsterx/ReGANSpace
Code DOI:10.5281/zenodo.6511501
Data URL:-
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Review URL:https://openreview.net/forum?id=BtZVD2f7n0F
Cite as:Dasu, V.A. and T.K., M.M. 2022. [Re] GANSpace: Discovering Interpretable GAN Controls. ReScience C 8, 2, #10.
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Davies, I. and Eglen, S. 2020. [Re] The principal components of natural images. ReScience C 6, 3, #6.

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Article (PDF):https://zenodo.org/record/4139359/files/article.pdf
Title:[Re] The principal components of natural images
Author(s):Davies, Iain and Eglen, Stephen
Journal:ReScience C
Year:2020
Month:oct
Volume:6
Issue:3
Number:#6
DOI:10.5281/zenodo.4139359
Code URL:https://github.com/IainDaviesMaths/Reproduction-Hancock.git
Code DOI:10.5281/zenodo.4139727
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Review URL:https://github.com/ReScience/submissions/issues/45
Cite as:Davies, I. and Eglen, S. 2020. [Re] The principal components of natural images. ReScience C 6, 3, #6.
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Davison, A.P. 2020. [Rp] Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model. ReScience C 6, 1, #14.

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Article (PDF):https://zenodo.org/record/3972130/files/article.pdf
Title:[Rp] Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model
Author(s):Davison, Andrew P.
Journal:ReScience C
Year:2020
Month:aug
Volume:6
Issue:1
Number:#14
DOI:10.5281/zenodo.3972130
Code URL:https://github.com/apdavison/bulbnet-reproduction
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Review URL:https://github.com/ReScience/submissions/issues/37
Cite as:Davison, A.P. 2020. [Rp] Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model. ReScience C 6, 1, #14.
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De Luisa, A. 2022. [Re] Thompson Sampling for Bandits with Clustered Arms. ReScience C 8, 2, #23.

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Article (PDF):https://zenodo.org/record/6574671/files/article.pdf
Title:[Re] Thompson Sampling for Bandits with Clustered Arms
Author(s):De Luisa, Andraž
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#23
DOI:10.5281/zenodo.6574671
Code URL:https://github.com/andrazdeluisa/reproducibility_challenge
Code DOI:10.5281/zenodo.6498328
Data URL:-
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Review URL:https://openreview.net/forum?id=r5LS3fmh0t
Cite as:De Luisa, A. 2022. [Re] Thompson Sampling for Bandits with Clustered Arms. ReScience C 8, 2, #23.
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Delsuc, M.-A. 2020. [Rp] Gifa V.4: A complete package for NMR data set processing. ReScience C 6, 1, #9.

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Title:[Rp] Gifa V.4: A complete package for NMR data set processing
Author(s):Delsuc, Marc-André
Journal:ReScience C
Year:2020
Month:jun
Volume:6
Issue:1
Number:#9
DOI:10.5281/zenodo.3904595
Code URL:https://github.com/delsuc/Gifa
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/33
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Deprez, H.L. gezegd, Rijsdijk, G., Rooij, B. de, and Zwerink, W. 2021. [Re] Reproducing ’Identifying through flows for recovering latent representations.’ ReScience C 7, 2, #17.

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Article (PDF):https://zenodo.org/record/4839595/files/article.pdf
Title:[Re] Reproducing ’Identifying through flows for recovering latent representations’
Author(s):gezegd Deprez, Hidde Lekanne and Rijsdijk, Geerten and de Rooij, Bart and Zwerink, Wouter
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#17
DOI:10.5281/zenodo.4839595
Code URL:https://github.com/HiddeLekanne/Reproducibility-Challenge-iFlow
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Review URL:https://openreview.net/forum?id=8jmIpypMzE
Cite as:Deprez, H.L. gezegd, Rijsdijk, G., Rooij, B. de, and Zwerink, W. 2021. [Re] Reproducing ’Identifying through flows for recovering latent representations.’ ReScience C 7, 2, #17.
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Devos, A., Chatel, S., and Grossglauser, M. 2019. [Re] Meta-learning with differentiable closed-form solvers. ReScience C 5, 2, #1.

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Article (PDF):https://zenodo.org/record/3160540/files/article.pdf
Title:[Re] Meta-learning with differentiable closed-form solvers
Author(s):Devos, Arnout and Chatel, Sylvain and Grossglauser, Matthias
Journal:ReScience C
Year:2019
Month:may
Volume:5
Issue:2
Number:#1
DOI:10.5281/zenodo.3160540
Code URL:https://github.com/ArnoutDevos/r2d2
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Review URL:https://github.com/reproducibility-challenge/iclr_2019/pull/150
Cite as:Devos, A., Chatel, S., and Grossglauser, M. 2019. [Re] Meta-learning with differentiable closed-form solvers. ReScience C 5, 2, #1.
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Dhane, F., Soeharjono, S., Stern, K., MacDonald, A., and Poisot, T. 2021. [Re] The Evolution of Virulence in Pathogens with Vertical and Horizontal Transmission. ReScience C 7, 1, #10.

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Title:[Re] The Evolution of Virulence in Pathogens with Vertical and Horizontal Transmission
Author(s):Dhane, Fares and Soeharjono, Sandrine and Stern, Kiri and MacDonald, Andrew and Poisot, Timothée
Journal:ReScience C
Year:2021
Month:nov
Volume:7
Issue:1
Number:#10
DOI:10.5281/zenodo.5722853
Code URL:https://github.com/BIO6032/2019_replication_LipstichEtAl_1996
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/56
Cite as:Dhane, F., Soeharjono, S., Stern, K., MacDonald, A., and Poisot, T. 2021. [Re] The Evolution of Virulence in Pathogens with Vertical and Horizontal Transmission. ReScience C 7, 1, #10.
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Di Cosmo, R. and Danelutto, M. 2020. [Rp] Reproducing and replicating the OCamlP3l experiment. ReScience C 6, 1, #2.

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Title:[Rp] Reproducing and replicating the OCamlP3l experiment
Author(s):Di Cosmo, Roberto and Danelutto, Marco
Journal:ReScience C
Year:2020
Month:apr
Volume:6
Issue:1
Number:#2
DOI:10.5281/zenodo.4041602
Code URL:https://archive.softwareheritage.org/swh:1:rev:2db189928c94d62a3b4757b3eec68f0a4d4113f0;origin=https://gitorious.org/ocamlp3l/ocamlp3l_cvs.git/
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/22
Cite as:Di Cosmo, R. and Danelutto, M. 2020. [Rp] Reproducing and replicating the OCamlP3l experiment. ReScience C 6, 1, #2.
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Didolkar, A. 2019. [Re] h-detach: Modifying the LSTM gradient towards better optimization. ReScience C 5, 2, #4.

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Title:[Re] h-detach: Modifying the LSTM gradient towards better optimization
Author(s):Didolkar, Aniket
Journal:ReScience C
Year:2019
Month:may
Volume:5
Issue:2
Number:#4
DOI:10.5281/zenodo.3162114
Code URL:https://github.com/dido1998/h-detach/tree/v1.0
Code DOI:10.5281/zenodo.2657361
Data URL:-
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Review URL:https://github.com/reproducibility-challenge/iclr_2019/pull/148
Cite as:Didolkar, A. 2019. [Re] h-detach: Modifying the LSTM gradient towards better optimization. ReScience C 5, 2, #4.
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Don, M., Chatterji, S., Kapralova, M., and Amaudruz, R. 2023. [Re] On the Reproducibility of "FairCal: Fairness Calibration for Face Verification". ReScience C 9, 2, #15.

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Article (PDF):https://zenodo.org/record/8173686/files/article.pdf
Title:[Re] On the Reproducibility of "FairCal: Fairness Calibration for Face Verification"
Author(s):Don, Marga and Chatterji, Satchit and Kapralova, Milena and Amaudruz, Ryan
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#15
DOI:10.5281/zenodo.8173686
Code URL:https://github.com/margajdon/reproduction-FAIRCAL
Code DOI:10.5281/zenodo.7941382
Data URL:-
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Review URL:https://openreview.net/forum?id=uVHUy7CWCL
Cite as:Don, M., Chatterji, S., Kapralova, M., and Amaudruz, R. 2023. [Re] On the Reproducibility of "FairCal: Fairness Calibration for Face Verification". ReScience C 9, 2, #15.
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Doyen, G., Picoche, C., and Barraquand, F. 2023. [Re] Biodiversity of plankton by species oscillations and chaos. ReScience C 9, 1, #4.

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Article (PDF):https://zenodo.org/record/10371655/files/article.pdf
Title:[Re] Biodiversity of plankton by species oscillations and chaos
Author(s):Doyen, Guillaume and Picoche, Coralie and Barraquand, Frédéric
Journal:ReScience C
Year:2023
Month:dec
Volume:9
Issue:1
Number:#4
DOI:10.5281/zenodo.10371655
Code URL:https://github.com/fbarraquand/supersaturated_coexistence
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Review URL:https://github.com/ReScience/submissions/issues/66
Cite as:Doyen, G., Picoche, C., and Barraquand, F. 2023. [Re] Biodiversity of plankton by species oscillations and chaos. ReScience C 9, 1, #4.
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Drabent, K., Wijnja, S., Sluijter, T., and Bereda, K. 2022. [Re] Replication study of "Privacy-preserving Collaborative Learning". ReScience C 8, 2, #11.

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Article (PDF):https://zenodo.org/record/6574647/files/article.pdf
Title:[Re] Replication study of "Privacy-preserving Collaborative Learning"
Author(s):Drabent, Karolina and Wijnja, Stefan and Sluijter, Thijs and Bereda, Konrad
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#11
DOI:10.5281/zenodo.6574647
Code URL:https://github.com/stfwn/ats-privacy-replication
Code DOI:10.5281/zenodo.6508136
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Review URL:https://openreview.net/forum?id=SY84JTG73CK
Cite as:Drabent, K., Wijnja, S., Sluijter, T., and Bereda, K. 2022. [Re] Replication study of "Privacy-preserving Collaborative Learning". ReScience C 8, 2, #11.
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Dubbeldam, E., Eijpe, A., Ruthardt, J., and Sasse, R. 2023. [Re] On the Reproducibility of CartoonX. ReScience C 9, 2, #10.

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Article (PDF):https://zenodo.org/record/8173672/files/article.pdf
Title:[Re] On the Reproducibility of CartoonX
Author(s):Dubbeldam, Elias and Eijpe, Aniek and Ruthardt, Jona and Sasse, Robin
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#10
DOI:10.5281/zenodo.8173672
Code URL:https://github.com/JonaRuthardt/MLRC-CartoonX
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=MK4IQJdLLeo
Cite as:Dubbeldam, E., Eijpe, A., Ruthardt, J., and Sasse, R. 2023. [Re] On the Reproducibility of CartoonX. ReScience C 9, 2, #10.
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Džubur, B. 2022. [Re] A Cluster-based Approach for Improving Isotropy in Contextual Embedding Space. ReScience C 8, 2, #12.

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Article (PDF):https://zenodo.org/record/6574649/files/article.pdf
Title:[Re] A Cluster-based Approach for Improving Isotropy in Contextual Embedding Space
Author(s):Džubur, Benjamin
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#12
DOI:10.5281/zenodo.6574649
Code URL:https://github.com/Benidzu/isotropy_reproduction
Code DOI:-
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Review URL:https://openreview.net/forum?id=rxWeB3zQ2CY
Cite as:Džubur, B. 2022. [Re] A Cluster-based Approach for Improving Isotropy in Contextual Embedding Space. ReScience C 8, 2, #12.
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Eaton, E. and Naghavi, P. 2022. [Re] Reproduction and Extension of "Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation". ReScience C 8, 2, #13.

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Article (PDF):https://zenodo.org/record/6574651/files/article.pdf
Title:[Re] Reproduction and Extension of "Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation"
Author(s):Eaton, Erica and Naghavi, Pirouz
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#13
DOI:10.5281/zenodo.6574651
Code URL:https://github.com/Pnaghavi/Mitigating-Gender-Bias-in-Generated-Text
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=StblE2MQ3AY
Cite as:Eaton, E. and Naghavi, P. 2022. [Re] Reproduction and Extension of "Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation". ReScience C 8, 2, #13.
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Eglen, S.J. 2021. [Re] Spatial constraints underlying the retinal mosaics of two types of horizontal cells in cat and macaque. ReScience C 6, 1, #22.

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Article (PDF):https://zenodo.org/record/5347786/files/article.pdf
Title:[Re] Spatial constraints underlying the retinal mosaics of two types of horizontal cells in cat and macaque
Author(s):Eglen, Stephen J.
Journal:ReScience C
Year:2021
Month:aug
Volume:6
Issue:1
Number:#22
DOI:10.5281/zenodo.5347786
Code URL:https://github.com/sje30/rescience-hor
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Review URL:https://github.com/ReScience/submissions/issues/34
Cite as:Eglen, S.J. 2021. [Re] Spatial constraints underlying the retinal mosaics of two types of horizontal cells in cat and macaque. ReScience C 6, 1, #22.
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Eijkelboom, F., Fokkema, M., Lau, A., and Verheijen, L. 2022. [Re] Reproduction Study of Variational Fair Clustering. ReScience C 8, 2, #14.

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Title:[Re] Reproduction Study of Variational Fair Clustering
Author(s):Eijkelboom, Floor and Fokkema, Mark and Lau, Anna and Verheijen, Luuk
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
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DOI:10.5281/zenodo.6574653
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Cite as:Eijkelboom, F., Fokkema, M., Lau, A., and Verheijen, L. 2022. [Re] Reproduction Study of Variational Fair Clustering. ReScience C 8, 2, #14.
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Enge, A. 2020. [Re] Volume computation for polytopes: Vingt ans après. ReScience C 6, 1, #17.

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Title:[Re] Volume computation for polytopes: Vingt ans après
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Cite as:Enge, A. 2020. [Re] Volume computation for polytopes: Vingt ans après. ReScience C 6, 1, #17.
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Erkol, M., Kınlı, F., Özcan, B., and Kıraç, F. 2023. [Re] Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization. ReScience C 9, 2, #2.

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Title:[Re] Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization
Author(s):Erkol, Mert and Kınlı, Furkan and Özcan, Barış and Kıraç, Furkan
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
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Etherington, T.R. and Lieske, D.J. 2019. [Re] Resampling methods for evaluating classification accuracy of wildlife habitat models. ReScience C 5, 1, #4.

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Title:[Re] Resampling methods for evaluating classification accuracy of wildlife habitat models
Author(s):Etherington, Thomas R. and Lieske, David J.
Journal:ReScience C
Year:2019
Month:may
Volume:5
Issue:1
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Cite as:Etherington, T.R. and Lieske, D.J. 2019. [Re] Resampling methods for evaluating classification accuracy of wildlife habitat models. ReScience C 5, 1, #4.
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Ferles, A., Nöu, A., and Valavanis, L. 2020. [Re] Zero-Shot Knowledge Transfer via Adversarial Belief Matching. ReScience C 6, 2, #2.

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Title:[Re] Zero-Shot Knowledge Transfer via Adversarial Belief Matching
Author(s):Ferles, Alexandros and Nöu, Alexander and Valavanis, Leonidas
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
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DOI:10.5281/zenodo.3818623
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Fuente, A.D. la and Aduviri, R. 2019. [Re] Variational Sparse Coding. ReScience C 5, 2, #2.

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Title:[Re] Variational Sparse Coding
Author(s):la Fuente, Alfredo De and Aduviri, Robert
Journal:ReScience C
Year:2019
Month:may
Volume:5
Issue:2
Number:#2
DOI:10.5281/zenodo.3161734
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Cite as:Fuente, A.D. la and Aduviri, R. 2019. [Re] Variational Sparse Coding. ReScience C 5, 2, #2.
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Galatolo, A. and Nilsson, A. 2022. [Re] Replicating and Improving GAN2Shape Through Novel Shape Priors and Training Steps. ReScience C 8, 2, #30.

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Title:[Re] Replicating and Improving GAN2Shape Through Novel Shape Priors and Training Steps
Author(s):Galatolo, Alessio and Nilsson, Alfred
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#30
DOI:10.5281/zenodo.6574685
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Review URL:https://openreview.net/forum?id=B8mxkTzX2RY
Cite as:Galatolo, A. and Nilsson, A. 2022. [Re] Replicating and Improving GAN2Shape Through Novel Shape Priors and Training Steps. ReScience C 8, 2, #30.
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Garcarz, S., Giorkatzi, A., Ivășchescu, A., and Pîslar, T.-M. 2023. [Re] Reproducibility Study: Label-Free Explainability for Unsupervised Models. ReScience C 9, 2, #16.

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Title:[Re] Reproducibility Study: Label-Free Explainability for Unsupervised Models
Author(s):Garcarz, Sławomir and Giorkatzi, Andreas and Ivășchescu, Ana and Pîslar, Theodora-Mara
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
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DOI:10.5281/zenodo.8173688
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Cite as:Garcarz, S., Giorkatzi, A., Ivășchescu, A., and Pîslar, T.-M. 2023. [Re] Reproducibility Study: Label-Free Explainability for Unsupervised Models. ReScience C 9, 2, #16.
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Garg, A. and Kagi, S.S. 2020. [Re] Hamiltonian Neural Networks. ReScience C 6, 2, #3.

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Title:[Re] Hamiltonian Neural Networks
Author(s):Garg, Ayush and Kagi, Sammed Shantinath
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#3
DOI:10.5281/zenodo.3818621
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Data URL:-
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Review URL:https://openreview.net/forum?id=HJxNSp9MTr
Cite as:Garg, A. and Kagi, S.S. 2020. [Re] Hamiltonian Neural Networks. ReScience C 6, 2, #3.
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Garg, P., Singhal, L., and Sardana, A. 2021. [Re] Training Binary Neural Networks using the Bayesian Learning Rule. ReScience C 7, 2, #5.

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Title:[Re] Training Binary Neural Networks using the Bayesian Learning Rule
Author(s):Garg, Prateek and Singhal, Lakshya and Sardana, Ashish
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#5
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Cite as:Garg, P., Singhal, L., and Sardana, A. 2021. [Re] Training Binary Neural Networks using the Bayesian Learning Rule. ReScience C 7, 2, #5.
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Geijn, C. van de, Kyriacou, V., Papadopoulou, I., and Vasileiou, V. 2022. [Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace. None 8, 2, #15.

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Title:[Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Author(s):van de Geijn, Chase and Kyriacou, Victor and Papadopoulou, Irene and Vasileiou, Vasiliki
Journal:None
Year:2022
Month:may
Volume:8
Issue:2
Number:#15
DOI:10.5281/zenodo.6574655
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Cite as:Geijn, C. van de, Kyriacou, V., Papadopoulou, I., and Vasileiou, V. 2022. [Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace. None 8, 2, #15.
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Geoffroy, F. 2021. [Re] Assortative matching and search. ReScience C 7, 1, #2.

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Title:[Re] Assortative matching and search
Author(s):Geoffroy, Félix
Journal:ReScience C
Year:2021
Month:mar
Volume:7
Issue:1
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DOI:10.5281/zenodo.4646680
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/47
Cite as:Geoffroy, F. 2021. [Re] Assortative matching and search. ReScience C 7, 1, #2.
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Gillard, T., Fix, J., and Dutech, A. 2022. [Re] Modeling habits as self-sustained patterns of sensorimotor behavior. ReScience C 8, 1, #2.

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Title:[Re] Modeling habits as self-sustained patterns of sensorimotor behavior
Author(s):Gillard, Tristan and Fix, Jérémy and Dutech, Alain
Journal:ReScience C
Year:2022
Month:apr
Volume:8
Issue:1
Number:#2
DOI:https://doi.org/10.5281/zenodo.6484021
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Cite as:Gillard, T., Fix, J., and Dutech, A. 2022. [Re] Modeling habits as self-sustained patterns of sensorimotor behavior. ReScience C 8, 1, #2.
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Gohil, V., Narayanan, S.D., and Jain, A. 2020. [Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. ReScience C 6, 2, #4.

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Title:[Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
Author(s):Gohil, Varun and Narayanan, S. Deepak and Jain, Atishay
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#4
DOI:10.5281/zenodo.3818619
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Cite as:Gohil, V., Narayanan, S.D., and Jain, A. 2020. [Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. ReScience C 6, 2, #4.
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Greven, J., Stallinga, S., and Seljee, Z. 2023. [Re] Reproducing FairCal: Fairness Calibration for Face Verification. ReScience C 9, 2, #28.

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Title:[Re] Reproducing FairCal: Fairness Calibration for Face Verification
Author(s):Greven, Jip and Stallinga, Simon and Seljee, Zirk
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#28
DOI:10.5281/zenodo.8173719
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Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=jDBYRwDpeW
Cite as:Greven, J., Stallinga, S., and Seljee, Z. 2023. [Re] Reproducing FairCal: Fairness Calibration for Face Verification. ReScience C 9, 2, #28.
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Habacker, R., Harrison, A., Parisot, M., and Snijders, A. 2021. [Re] Reproducing Learning to Deceive With Attention-Based Explanations. ReScience C 7, 2, #6.

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Title:[Re] Reproducing Learning to Deceive With Attention-Based Explanations
Author(s):Habacker, Rahel and Harrison, Andrew and Parisot, Mathias and Snijders, Ard
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
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DOI:10.5281/zenodo.4834146
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Review URL:https://openreview.net/forum?id=-rn9m0Gt6AQ
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Hardy, I. 2022. [Re] An Implementation of Fair Robust Learning. ReScience C 8, 2, #16.

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Hentschke, H. 2020. [Re] Hippocampal Phase-Amplitude Coupling unearthed again. ReScience C 6, 3, #3.

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Hinsen, K. 2020. [Rp] Structural flexibility in proteins - impact of the crystal environment. ReScience C 6, 1, #5.

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Journal:ReScience C
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Hinsen, K. 2020. [¬Rp] Stokes drag on conglomerates of spheres. ReScience C 6, 1, #7.

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Holdijk, L., Boon, M., Henckens, S., and Jong, L. de. 2021. [Re] Parameterized Explainer for Graph Neural Network. ReScience C 7, 2, #7.

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Journal:ReScience C
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Höppe, T., Miszkurka, A., and Wilkman, D.B. 2022. [Re] Understanding Self-Supervised Learning Dynamics without Contrastive Pairs. ReScience C 8, 2, #17.

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Hu, A., Ranum, O., Pozrikidou, C., and Zhou, M. 2023. [Re] Reproducibility study of Joint Multisided Exposure Fairness for Recommendation. ReScience C 9, 2, #20.

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Journal:ReScience C
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Hudovernik, V., Rot, Ž., Vovk, K., Škodnik, L., and Zajc, L.Č. 2026. Learning with Noisy Labels [ Re]visited. ReScience C 11, 1, #2.

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Jiles, R. and Chakraborty, M. 2022. [Re] Domain Generalization using Causal Matching. ReScience C 8, 2, #18.

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Year:2022
Month:may
Volume:8
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Kim, S.S.Y., Zhang, S., Meister, N., and Russakovsky, O. 2021. [Re] Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias. ReScience C 7, 2, #8.

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Title:[Re] Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias
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Journal:ReScience C
Year:2021
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Volume:7
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Review URL:https://openreview.net/forum?id=PRXM8-O9PKd
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Kirca, I.-A., Hamerslag, D., Baas, A., and Prent, J. 2022. [¬Re] Reproducibility Study of ’Exacerbating Algorithmic Bias through Fairness Attacks’ . ReScience C 8, 2, #19.

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Title:[¬Re] Reproducibility Study of ’Exacerbating Algorithmic Bias through Fairness Attacks’
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Year:2022
Month:may
Volume:8
Issue:2
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Cite as:Kirca, I.-A., Hamerslag, D., Baas, A., and Prent, J. 2022. [¬Re] Reproducibility Study of ’Exacerbating Algorithmic Bias through Fairness Attacks’ . ReScience C 8, 2, #19.
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Kireev, K., Mohtashami, A., and Pajouheshgar, E. 2021. [Re] Warm-Starting Neural Network Training. ReScience C 7, 2, #14.

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Title:[Re] Warm-Starting Neural Network Training
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Journal:ReScience C
Year:2021
Month:may
Volume:7
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Kljun, M., Teršek, M., and Vreš, D. 2022. [Re] Learning to count everything. ReScience C 8, 2, #39.

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Year:2022
Month:may
Volume:8
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Cite as:Kljun, M., Teršek, M., and Vreš, D. 2022. [Re] Learning to count everything. ReScience C 8, 2, #39.
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Kolkman, G., Athmer, J., Labro, A., and Kulicki, M. 2022. [Re] Strategic classification made practical: reproduction. ReScience C 8, 2, #20.

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Article (PDF):https://zenodo.org/record/6574665/files/article.pdf
Title:[Re] Strategic classification made practical: reproduction
Author(s):Kolkman, Guilly and Athmer, Jan and Labro, Alex and Kulicki, Maksymilian
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#20
DOI:10.5281/zenodo.6574665
Code URL:https://github.com/GuillyK/FACT-ai
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Data URL:-
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Review URL:https://openreview.net/forum?id=rNgg03fXnRY
Cite as:Kolkman, G., Athmer, J., Labro, A., and Kulicki, M. 2022. [Re] Strategic classification made practical: reproduction. ReScience C 8, 2, #20.
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Kviman, O., Nilsson, L., and Larsson, M. 2020. [Re] Tensor Monte Carlo: Particle Methods for the GPU Era. ReScience C 6, 2, #5.

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Article (PDF):https://zenodo.org/record/3818617/files/article.pdf
Title:[Re] Tensor Monte Carlo: Particle Methods for the GPU Era
Author(s):Kviman, Oskar and Nilsson, Linus and Larsson, Martin
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#5
DOI:10.5281/zenodo.3818617
Code URL:https://github.com/LinuNils/TMC_reproduced
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Data URL:-
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Review URL:https://openreview.net/forum?id=BJxUSaczTH
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Kyrylov, V., Bedi, N.S., and Zang, Q. 2023. [Re] VAE Approximation Error: ELBO and Exponential Families. ReScience C 9, 2, #37.

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Article (PDF):https://zenodo.org/record/8173745/files/article.pdf
Title:[Re] VAE Approximation Error: ELBO and Exponential Families
Author(s):Kyrylov, Volodymyr and Bedi, Navdeep Singh and Zang, Qianbo
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#37
DOI:10.5281/zenodo.8173745
Code URL:https://github.com/proger/vae
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Review URL:https://openreview.net/forum?id=ozbAwipuZu
Cite as:Kyrylov, V., Bedi, N.S., and Zang, Q. 2023. [Re] VAE Approximation Error: ELBO and Exponential Families. ReScience C 9, 2, #37.
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Langezaal, E.R., Belleman, J., Veenboer, T., and Noorthoek, J. 2023. [Re] Label-Free Explainability for Unsupervised Models. ReScience C 9, 2, #4.

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Article (PDF):https://zenodo.org/record/8173656/files/article.pdf
Title:[Re] Label-Free Explainability for Unsupervised Models
Author(s):Langezaal, Eric Robin and Belleman, Jesse and Veenboer, Tim and Noorthoek, Joeri
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#4
DOI:10.5281/zenodo.8173656
Code URL:https://github.com/EricLangezaal/Re-Label-Free-XAI
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Review URL:https://openreview.net/forum?id=bBVZ3pY4z8p
Cite as:Langezaal, E.R., Belleman, J., Veenboer, T., and Noorthoek, J. 2023. [Re] Label-Free Explainability for Unsupervised Models. ReScience C 9, 2, #4.
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Larisch, R. 2019. [Re] Connectivity reflects coding a model of voltage-based STDP with homeostasis. ReScience C 5, 3, #2.

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Article (PDF):https://zenodo.org/record/3538217/files/article.pdf
Title:[Re] Connectivity reflects coding a model of voltage-based STDP with homeostasis
Author(s):Larisch, Rene
Journal:ReScience C
Year:2019
Month:nov
Volume:5
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DOI:10.5281/zenodo.3538217
Code URL:https://github.com/rLarisch/ReScience-submission/tree/Larisch-2019/code
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Review URL:https://github.com/ReScience/ReScience-submission/pull/57#issuecomment-549728501
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Leblois, A. 2021. [Re] Reproduction of the normal and pathological dynamics in the basal ganglia-thalamo-cortical network. ReScience C 6, 1, #19.

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Article (PDF):https://zenodo.org/record/4543356/files/article.pdf
Title:[Re] Reproduction of the normal and pathological dynamics in the basal ganglia-thalamo-cortical network
Author(s):Leblois, Arthur
Journal:ReScience C
Year:2021
Month:feb
Volume:6
Issue:1
Number:#19
DOI:10.5281/zenodo.4543356
Code URL:https://github.com/aleblois/BGdynamics2006/blob/master/Copie%20de%20simdelai2boucles_all2all_GPe.c
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Review URL:https://github.com/ReScience/submissions/issues/28
Cite as:Leblois, A. 2021. [Re] Reproduction of the normal and pathological dynamics in the basal ganglia-thalamo-cortical network. ReScience C 6, 1, #19.
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Lécuyer, F., Danisch, M., and Tabourier, L. 2021. [Re] Speedup Graph Processing by Graph Ordering. ReScience C 7, 1, #3.

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Article (PDF):https://zenodo.org/record/4836230/files/article.pdf
Title:[Re] Speedup Graph Processing by Graph Ordering
Author(s):Lécuyer, Fabrice and Danisch, Maximilien and Tabourier, Lionel
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:1
Number:#3
DOI:10.5281/zenodo.4836230
Code URL:https://github.com/lecfab/rescience-gorder
Code DOI:-
Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/52
Cite as:Lécuyer, F., Danisch, M., and Tabourier, L. 2021. [Re] Speedup Graph Processing by Graph Ordering. ReScience C 7, 1, #3.
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Lee, S.R. and Lee, S.B. 2023. [Re] Pure Noise to the Rescue of Insufficient Data. ReScience C 9, 2, #45.

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Article (PDF):https://zenodo.org/record/8173763/files/article.pdf
Title:[Re] Pure Noise to the Rescue of Insufficient Data
Author(s):Lee, Seungjae Ryan and Lee, Seungmin Brian
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#45
DOI:10.5281/zenodo.8173763
Code URL:https://github.com/seungjaeryanlee/pure-noise
Code DOI:10.5281/zenodo.7947264
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Review URL:https://openreview.net/forum?id=ErBe4MnsVD
Cite as:Lee, S.R. and Lee, S.B. 2023. [Re] Pure Noise to the Rescue of Insufficient Data. ReScience C 9, 2, #45.
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Legrand, A. and Velho, P. 2023. [Re] Velho and Legrand (2009) - Accuracy Study and Improvement of Network Simulation in the SimGrid Framework. ReScience C 6, 1, #20.

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Article (PDF):https://zenodo.org/record/10275726/files/article.pdf
Title:[Re] Velho and Legrand (2009) - Accuracy Study and Improvement of Network Simulation in the SimGrid Framework
Author(s):Legrand, Arnaud and Velho, Pedro
Journal:ReScience C
Year:2023
Month:dec
Volume:6
Issue:1
Number:#20
DOI:10.5281/zenodo.10275726
Code URL:https://github.com/alegrand/reproducibility-challenge
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Review URL:https://github.com/ReScience/submissions/issues/39
Cite as:Legrand, A. and Velho, P. 2023. [Re] Velho and Legrand (2009) - Accuracy Study and Improvement of Network Simulation in the SimGrid Framework. ReScience C 6, 1, #20.
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Lemmens, J., Jancura, P., Dubbelman, G., and Elrofai, H. 2023. [Re] Object Detection Meets Knowledge Graphs. ReScience C 9, 1, #1.

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Article (PDF):https://zenodo.org/record/7800679/files/article.pdf
Title:[Re] Object Detection Meets Knowledge Graphs
Author(s):Lemmens, Jarl and Jancura, Pavol and Dubbelman, Gijs and Elrofai, Hala
Journal:ReScience C
Year:2023
Month:mar
Volume:9
Issue:1
Number:#1
DOI:10.5281/zenodo.7800679
Code URL:https://github.com/tue-mps/rescience-ijcai2017-230
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Data URL:https://zenodo.org/record/7385730#.Y73csnbMJPY
Data DOI:10.5281/zenodo.7385730
Review URL:https://github.com/ReScience/submissions/issues/59
Cite as:Lemmens, J., Jancura, P., Dubbelman, G., and Elrofai, H. 2023. [Re] Object Detection Meets Knowledge Graphs. ReScience C 9, 1, #1.
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Li, C., Tu, R., and Zhang, H. 2021. [Re] Reimplementation of FixMatch and Investigation on Noisy (Pseudo) Labels and Confirmation Errors of FixMatch. ReScience C 7, 2, #9.

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Article (PDF):https://zenodo.org/record/4834442/files/article.pdf
Title:[Re] Reimplementation of FixMatch and Investigation on Noisy (Pseudo) Labels and Confirmation Errors of FixMatch
Author(s):Li, Ci and Tu, Ruibo and Zhang, Hui
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#9
DOI:10.5281/zenodo.4834442
Code URL:https://github.com/Celiali/FixMatch.git
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=3VXeifKSaTE
Cite as:Li, C., Tu, R., and Zhang, H. 2021. [Re] Reimplementation of FixMatch and Investigation on Noisy (Pseudo) Labels and Confirmation Errors of FixMatch. ReScience C 7, 2, #9.
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Liiv, T., Lennelöv, E., and Norén, A. 2021. [Re] A Reproduction of Ensemble Distribution Distillation. ReScience C 7, 2, #10.

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Article (PDF):https://zenodo.org/record/4834516/files/article.pdf
Title:[Re] A Reproduction of Ensemble Distribution Distillation
Author(s):Liiv, Toomas and Lennelöv, Einar and Norén, Aron
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#10
DOI:10.5281/zenodo.4834516
Code URL:https://github.com/lennelov/endd-reproduce
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=p1BXNUcTFsN
Cite as:Liiv, T., Lennelöv, E., and Norén, A. 2021. [Re] A Reproduction of Ensemble Distribution Distillation. ReScience C 7, 2, #10.
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Liljefors, F., Sorkhei, M., and Broomé, S. 2020. [Re] Unsupervised Scalable Representation Learning for Multivariate Time Series. ReScience C 6, 2, #6.

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Article (PDF):https://zenodo.org/record/3818613/files/article.pdf
Title:[Re] Unsupervised Scalable Representation Learning for Multivariate Time Series
Author(s):Liljefors, Felix and Sorkhei, Moein and Broomé, Sofia
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#6
DOI:10.5281/zenodo.3818613
Code URL:https://github.com/lilfelix/reproducibility_NeurIPS19
Code DOI:-
Data URL:-
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Review URL:https://openreview.net/forum?id=HyxQr65z6S
Cite as:Liljefors, F., Sorkhei, M., and Broomé, S. 2020. [Re] Unsupervised Scalable Representation Learning for Multivariate Time Series. ReScience C 6, 2, #6.
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Lima, V., Shimoura, R.O., Kamiji, N.L., Battaglia, D., and Roque, A.C. 2023. [Re] Inter-areal Balanced Amplification Enhances Signal Propagation in a Large-Scale Circuit Model of the Primate Cortex. ReScience C 9, 1, #3.

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Article (PDF):https://zenodo.org/record/10257800/files/article.pdf
Title:[Re] Inter-areal Balanced Amplification Enhances Signal Propagation in a Large-Scale Circuit Model of the Primate Cortex
Author(s):Lima, Vinicius and Shimoura, Renan O. and Kamiji, Nilton L. and Battaglia, Demian and Roque, Antonio C.
Journal:ReScience C
Year:2023
Month:dec
Volume:9
Issue:1
Number:#3
DOI:10.5281/zenodo.10257800
Code URL:https://github.com/ViniciusLima94/ReScience-Joglekar/tree/master/code
Code DOI:-
Data URL:https://github.com/ViniciusLima94/ReScience-Joglekar/tree/master/code/interareal
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/72
Cite as:Lima, V., Shimoura, R.O., Kamiji, N.L., Battaglia, D., and Roque, A.C. 2023. [Re] Inter-areal Balanced Amplification Enhances Signal Propagation in a Large-Scale Circuit Model of the Primate Cortex. ReScience C 9, 1, #3.
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Liu, Y., Xu, J., and Pan, Y. 2020. [Re] When to Trust Your Model: Model-Based Policy Optimization. ReScience C 6, 2, #7.

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Article (PDF):https://zenodo.org/record/3818611/files/article.pdf
Title:[Re] When to Trust Your Model: Model-Based Policy Optimization
Author(s):Liu, Yuting and Xu, Jiahao and Pan, Yiming
Journal:ReScience C
Year:2020
Month:may
Volume:6
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Number:#7
DOI:10.5281/zenodo.3818611
Code URL:https://github.com/jxu43/replication-mbpo
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=rkezvT9f6r
Cite as:Liu, Y., Xu, J., and Pan, Y. 2020. [Re] When to Trust Your Model: Model-Based Policy Optimization. ReScience C 6, 2, #7.
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Livernoche, V. and Sujaya, V. 2023. [Re] A Reproduction of Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification. ReScience C 9, 2, #33.

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Article (PDF):https://zenodo.org/record/8173735/files/article.pdf
Title:[Re] A Reproduction of Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification
Author(s):Livernoche, Victor and Sujaya, Vidya
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#33
DOI:10.5281/zenodo.8173735
Code URL:https://github.com/vicliv/AMuLaP-Reproduction
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=t8ZZ2Y356Ix
Cite as:Livernoche, V. and Sujaya, V. 2023. [Re] A Reproduction of Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification. ReScience C 9, 2, #33.
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Maggi, S. 2020. [Rp] Reproduction of Step width enhancement in a pulse-driven Josephson junction. ReScience C 6, 1, #10.

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Article (PDF):https://zenodo.org/record/3922195/files/article.pdf
Title:[Rp] Reproduction of Step width enhancement in a pulse-driven Josephson junction
Author(s):Maggi, Sabino
Journal:ReScience C
Year:2020
Month:jun
Volume:6
Issue:1
Number:#10
DOI:10.5281/zenodo.3922195
Code URL:https://github.com/sabinomaggi/ten-years-challenge-pulsed-drive
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/23
Cite as:Maggi, S. 2020. [Rp] Reproduction of Step width enhancement in a pulse-driven Josephson junction. ReScience C 6, 1, #10.
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Maheshwari, D. 2025. [Re] BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning. ReScience C 10, 1, #2.

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Article (PDF):https://zenodo.org/record/14964875/files/article.pdf
Title:[Re] BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning
Author(s):Maheshwari, Disha
Journal:ReScience C
Year:2025
Month:mar
Volume:10
Issue:1
Number:#2
DOI:10.5281/zenodo.14964875
Code URL:https://github.com/disha101003/ReScience
Code DOI:-
Data URL:https://www.cs.toronto.edu/ kriz/cifar.html
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/85
Cite as:Maheshwari, D. 2025. [Re] BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning. ReScience C 10, 1, #2.
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Mahlau, Y., Kayser, L., and Berg, L. 2023. [Re] On Explainability of Graph Neural Networks via Subgraph Explorations. ReScience C 9, 2, #41.

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Article (PDF):https://zenodo.org/record/8173753/files/article.pdf
Title:[Re] On Explainability of Graph Neural Networks via Subgraph Explorations
Author(s):Mahlau, Yannik and Kayser, Leonie and Berg, Lukas
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#41
DOI:10.5281/zenodo.8173753
Code URL:https://github.com/ymahlau/subgraphx
Code DOI:https://zenodo.org/badge/latestdoi/637344138
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=zKBJw4Ht8s
Cite as:Mahlau, Y., Kayser, L., and Berg, L. 2023. [Re] On Explainability of Graph Neural Networks via Subgraph Explorations. ReScience C 9, 2, #41.
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Marini, L., Nabeel, M., and Loiko, A. 2023. [Re] Intriguing Properties of Contrastive Losses. ReScience C 9, 2, #6.

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Article (PDF):https://zenodo.org/record/8173662/files/article.pdf
Title:[Re] Intriguing Properties of Contrastive Losses
Author(s):Marini, Luca and Nabeel, Mohamad and Loiko, Alexandre
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#6
DOI:10.5281/zenodo.8173662
Code URL:https://github.com/mona251/Intriguing-Properties-of-Contrastive-Losses
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=gb71irTNN7
Cite as:Marini, L., Nabeel, M., and Loiko, A. 2023. [Re] Intriguing Properties of Contrastive Losses. ReScience C 9, 2, #6.
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Martorella, T., Contreras, H.M.R., and García, D.C. 2023. [Re] Numerical influence of ReLU’(0) on backpropagation. ReScience C 9, 2, #17.

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Article (PDF):https://zenodo.org/record/8173692/files/article.pdf
Title:[Re] Numerical influence of ReLU’(0) on backpropagation
Author(s):Martorella, Tommaso and Contreras, Héctor Manuel Ramirez and García, Daniel Cerezo
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#17
DOI:10.5281/zenodo.8173692
Code URL:https://github.com/CS-433/ml-project-2-ristrettolearning-2
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=YAWQTQZVoA
Cite as:Martorella, T., Contreras, H.M.R., and García, D.C. 2023. [Re] Numerical influence of ReLU’(0) on backpropagation. ReScience C 9, 2, #17.
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Mast, D. van der, Haddou, S.B., Chu, J., and Stefels, J. 2022. [Re] Replication Study of "Fairness and Bias in Online Selection". None 8, 2, #24.

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Article (PDF):https://zenodo.org/record/6574673/files/article.pdf
Title:[Re] Replication Study of "Fairness and Bias in Online Selection"
Author(s):van der Mast, Diego and Haddou, Soufiane Ben and Chu, Jacky and Stefels, Jaap
Journal:None
Year:2022
Month:may
Volume:8
Issue:2
Number:#24
DOI:10.5281/zenodo.6574673
Code URL:https://github.com/Di-ayy-go/fact-ai
Code DOI:10.5281/zenodo.6518051
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=SNeep2MXn0K
Cite as:Mast, D. van der, Haddou, S.B., Chu, J., and Stefels, J. 2022. [Re] Replication Study of "Fairness and Bias in Online Selection". None 8, 2, #24.
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Matosevic, A., Hein, E., and Nuzzo, F. 2020. [Re] Generative Modeling by Estimating Gradients of the Data Distribution. ReScience C 6, 2, #8.

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Article (PDF):https://zenodo.org/record/3818609/files/article.pdf
Title:[Re] Generative Modeling by Estimating Gradients of the Data Distribution
Author(s):Matosevic, Antonio and Hein, Eliisabet and Nuzzo, Francesco
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#8
DOI:10.5281/zenodo.3818609
Code URL:https://github.com/Xemnas0/NCSN-TF2.0
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=B1lcYrBgLH
Cite as:Matosevic, A., Hein, E., and Nuzzo, F. 2020. [Re] Generative Modeling by Estimating Gradients of the Data Distribution. ReScience C 6, 2, #8.
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Maurel, D., Fillioux, J., and Gugenheim, D. 2022. [Re] Effective Program Debloating via Reinforcement Learning. ReScience C 8, 1, #1.

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Article (PDF):https://zenodo.org/record/6255131/files/article.pdf
Title:[Re] Effective Program Debloating via Reinforcement Learning
Author(s):Maurel, Denis and Fillioux, Jérôme and Gugenheim, Dan
Journal:ReScience C
Year:2022
Month:mar
Volume:8
Issue:1
Number:#1
DOI:10.5281/zenodo.6255131
Code URL:https://gitlab.com/onepoint/recherche-et-developpement/optimus/chisel-replication
Code DOI:10.5281/zenodo.4530318
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/48
Cite as:Maurel, D., Fillioux, J., and Gugenheim, D. 2022. [Re] Effective Program Debloating via Reinforcement Learning. ReScience C 8, 1, #1.
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McBane, G.C. 2020. [Rp] Reproduction of interaction second virial coefficient calculation for H_2–CO interactions [J. Chem. Phys. vol. 112, 4417 (2000)]. ReScience C 6, 1, #1.

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Article (PDF):https://zenodo.org/record/3630224/files/article.pdf
Title:[Rp] Reproduction of interaction second virial coefficient calculation for H_2–CO interactions [J. Chem. Phys. vol. 112, 4417 (2000)]
Author(s):McBane, George C.
Journal:ReScience C
Year:2020
Month:jan
Volume:6
Issue:1
Number:#1
DOI:10.5281/zenodo.3630224
Code URL:http://faculty.gvsu.edu/mcbaneg/virial6-resciencec.zip
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/11
Cite as:McBane, G.C. 2020. [Rp] Reproduction of interaction second virial coefficient calculation for H_2–CO interactions [J. Chem. Phys. vol. 112, 4417 (2000)]. ReScience C 6, 1, #1.
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McLeish, S. and Tran-Thanh, L. 2023. [Re] End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. ReScience C 9, 2, #3.

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Article (PDF):https://zenodo.org/record/8173654/files/article.pdf
Title:[Re] End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking
Author(s):McLeish, Sean and Tran-Thanh, Long
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#3
DOI:10.5281/zenodo.8173654
Code URL:https://github.com/mcleish7/MLRC-deep-thinking
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=WaZB4pUVTi
Cite as:McLeish, S. and Tran-Thanh, L. 2023. [Re] End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. ReScience C 9, 2, #3.
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Mehta, A., Uppal, K., Jadhav, K., Natarajan, M., Agrawal, M., and Chakravarty, D. 2022. [Re] Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation. ReScience C 8, 2, #26.

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Article (PDF):https://zenodo.org/record/6574677/files/article.pdf
Title:[Re] Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation
Author(s):Mehta, Aryan and Uppal, Karan and Jadhav, Kaushal and Natarajan, Monish and Agrawal, Mradul and Chakravarty, Debashish
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#26
DOI:10.5281/zenodo.6574677
Code URL:https://github.com/karan-uppal3/BANA
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=rUQllTGQhAY
Cite as:Mehta, A., Uppal, K., Jadhav, K., Natarajan, M., Agrawal, M., and Chakravarty, D. 2022. [Re] Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation. ReScience C 8, 2, #26.
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Menteş, S., Kınlı, F., Özcan, B., and Kıraç, F. 2021. [Re] Spatial-Adaptive Network for Single Image Denoising. ReScience C 7, 2, #12.

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Article (PDF):https://zenodo.org/record/4834672/files/article.pdf
Title:[Re] Spatial-Adaptive Network for Single Image Denoising
Author(s):Menteş, Sami and Kınlı, Furkan and Özcan, Barış and Kıraç, Furkan
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#12
DOI:10.5281/zenodo.4834672
Code URL:https://github.com/sami-automatic/SADNet_Replication
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=yiAI9QN9nYt¬eId=SMFjCY6qG8
Cite as:Menteş, S., Kınlı, F., Özcan, B., and Kıraç, F. 2021. [Re] Spatial-Adaptive Network for Single Image Denoising. ReScience C 7, 2, #12.
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Merk, D., Smit, D., Beukers, B., and Mendsuren, T. 2023. [Re] Reproducibility Study of ”Latent Space Smoothing for Individually Fair Representations.” ReScience C 9, 2, #30.

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Article (PDF):https://zenodo.org/record/8173725/files/article.pdf
Title:[Re] Reproducibility Study of ”Latent Space Smoothing for Individually Fair Representations”
Author(s):Merk, Didier and Smit, Denny and Beukers, Boaz and Mendsuren, Tsatsral
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#30
DOI:10.5281/zenodo.8173725
Code URL:https://github.com/Mametchiii/lassi-reproducibility
Code DOI:10.5281/zenodo.7950717
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=J-Lgb7Vc0wX
Cite as:Merk, D., Smit, D., Beukers, B., and Mendsuren, T. 2023. [Re] Reproducibility Study of ”Latent Space Smoothing for Individually Fair Representations.” ReScience C 9, 2, #30.
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Mesnard, O. and Barba, L.A. 2021. [Re] Three-dimensional wake topology and propulsive performance of low-aspect-ratio pitching-rolling plates. ReScience C 7, 1, #7.

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Article (PDF):https://zenodo.org/record/5234931/files/article.pdf
Title:[Re] Three-dimensional wake topology and propulsive performance of low-aspect-ratio pitching-rolling plates
Author(s):Mesnard, Olivier and Barba, Lorena A.
Journal:ReScience C
Year:2021
Month:aug
Volume:7
Issue:1
Number:#7
DOI:10.5281/zenodo.5234931
Code URL:https://github.com/barbagroup/petibm-rollingpitching
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/55
Cite as:Mesnard, O. and Barba, L.A. 2021. [Re] Three-dimensional wake topology and propulsive performance of low-aspect-ratio pitching-rolling plates. ReScience C 7, 1, #7.
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Mikler, S. 2022. [Re] Reproducibility Study: Comparing Rewinding and Fine-tuning in Neural Network Pruning. ReScience C 8, 2, #27.

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Article (PDF):https://zenodo.org/record/6574679/files/article.pdf
Title:[Re] Reproducibility Study: Comparing Rewinding and Fine-tuning in Neural Network Pruning
Author(s):Mikler, Szymon
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#27
DOI:10.5281/zenodo.6574679
Code URL:https://github.com/gahaalt/reproducing-comparing-rewinding-and-finetuning
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Review URL:https://openreview.net/forum?id=HxWEL2zQ3AK
Cite as:Mikler, S. 2022. [Re] Reproducibility Study: Comparing Rewinding and Fine-tuning in Neural Network Pruning. ReScience C 8, 2, #27.
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Misiek, T. and Khamassi, M. 2022. [Re] A general model of hippocampal and dorsal striatal learning and decision making. ReScience C 8, 1, #4.

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Title:[Re] A general model of hippocampal and dorsal striatal learning and decision making
Author(s):Misiek, Thomas and Khamassi, Mehdi
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:1
Number:#4
DOI:10.5281/zenodo.6573684
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Code DOI:10.5281/zenodo.6551722
Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/62
Cite as:Misiek, T. and Khamassi, M. 2022. [Re] A general model of hippocampal and dorsal striatal learning and decision making. ReScience C 8, 1, #4.
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Mizrahi, D., Yüksel, O.K., and Kyzy, A.M. 2021. [Re] Can gradient clipping mitigate label noise? ReScience C 7, 2, #13.

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Title:[Re] Can gradient clipping mitigate label noise?
Author(s):Mizrahi, David and Yüksel, Oğuz Kaan and Kyzy, Aiday Marlen
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#13
DOI:10.5281/zenodo.4834744
Code URL:https://github.com/dmizr/phuber
Code DOI:-
Data URL:-
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Review URL:https://openreview.net/forum?id=TM_SgwWJA23
Cite as:Mizrahi, D., Yüksel, O.K., and Kyzy, A.M. 2021. [Re] Can gradient clipping mitigate label noise? ReScience C 7, 2, #13.
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Moalla, S., Madeira, M., Riccio, L., and Lee, J. 2023. [Re] Reproducibility Study of Behavior Transformers. ReScience C 9, 2, #43.

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Title:[Re] Reproducibility Study of Behavior Transformers
Author(s):Moalla, Skander and Madeira, Manuel and Riccio, Lorenzo and Lee, Joonhyung
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#43
DOI:10.5281/zenodo.8173757
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Review URL:https://openreview.net/forum?id=E0qO5dI5aEn
Cite as:Moalla, S., Madeira, M., Riccio, L., and Lee, J. 2023. [Re] Reproducibility Study of Behavior Transformers. ReScience C 9, 2, #43.
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Moens, G.J., Witte, J. de, Göbel, T.P., and Oever, M. van den. 2023. [Re] CrossWalk Fairness-enhanced Node Representation Learning. ReScience C 9, 2, #38.

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Title:[Re] CrossWalk Fairness-enhanced Node Representation Learning
Author(s):Moens, Gijs Joppe and de Witte, Job and Göbel, Tobias Pieter and van den Oever, Meggie
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#38
DOI:10.5281/zenodo.8173747
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Cite as:Moens, G.J., Witte, J. de, Göbel, T.P., and Oever, M. van den. 2023. [Re] CrossWalk Fairness-enhanced Node Representation Learning. ReScience C 9, 2, #38.
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Mohorčič, D. and Ocepek, D. 2023. [Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods. ReScience C 9, 2, #19.

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Title:[Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods
Author(s):Mohorčič, Domen and Ocepek, David
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#19
DOI:10.5281/zenodo.8173696
Code URL:https://github.com/do8572/MLDS
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Review URL:https://openreview.net/forum?id=NgPQSqpz-Y
Cite as:Mohorčič, D. and Ocepek, D. 2023. [Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods. ReScience C 9, 2, #19.
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Morita, K. 2023. [Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles. ReScience C 9, 2, #12.

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Title:[Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles
Author(s):Morita, Kyosuke
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#12
DOI:10.5281/zenodo.8173678
Code URL:https://github.com/kyosek/focus-reproducibility
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Review URL:https://openreview.net/forum?id=n1q-iz83S5¬eId=60kzDmcWau
Cite as:Morita, K. 2023. [Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles. ReScience C 9, 2, #12.
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Nalmpantis, A., Panagiotopoulos, A., Gkountouras, J., and Papakostas, K. 2022. [Re] Exacerbating Algorithmic Bias through Fairness Attacks. None 8, 2, #28.

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Title:[Re] Exacerbating Algorithmic Bias through Fairness Attacks
Author(s):Nalmpantis, Angelos and Panagiotopoulos, Apostolos and Gkountouras, John and Papakostas, Konstantinos
Journal:None
Year:2022
Month:may
Volume:8
Issue:2
Number:#28
DOI:10.5281/zenodo.6574681
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Data URL:-
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Review URL:https://openreview.net/forum?id=rYLMJ6zX3RF
Cite as:Nalmpantis, A., Panagiotopoulos, A., Gkountouras, J., and Papakostas, K. 2022. [Re] Exacerbating Algorithmic Bias through Fairness Attacks. None 8, 2, #28.
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Nayak, N., Raj, V., and Kalyani, S. 2020. [Re] A comprehensive study on binary optimizer and its applicability. ReScience C 6, 2, #9.

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Article (PDF):https://zenodo.org/record/3818607/files/article.pdf
Title:[Re] A comprehensive study on binary optimizer and its applicability
Author(s):Nayak, Nancy and Raj, Vishnu and Kalyani, Sheetal
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#9
DOI:10.5281/zenodo.3818607
Code URL:https://github.com/nancy-nayak/rethinking-bnn
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=y53aaSM5o
Cite as:Nayak, N., Raj, V., and Kalyani, S. 2020. [Re] A comprehensive study on binary optimizer and its applicability. ReScience C 6, 2, #9.
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Neplenbroek, V., Perdijk, S., and Prins, V. 2022. [Re] Replication study of ’Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling.’ ReScience C 8, 2, #29.

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Article (PDF):https://zenodo.org/record/6574683/files/article.pdf
Title:[Re] Replication study of ’Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling’
Author(s):Neplenbroek, Vera and Perdijk, Sabijn and Prins, Victor
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#29
DOI:10.5281/zenodo.6574683
Code URL:https://github.com/Veranep/rideshare-replication
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Cite as:Neplenbroek, V., Perdijk, S., and Prins, V. 2022. [Re] Replication study of ’Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling.’ ReScience C 8, 2, #29.
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Obadage, R.R., Thennakoon, K., Rajtmajer, S.M., and Wu, J. 2025. [Re] Network Deconvolution. ReScience C 10, 1, #4.

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Title:[Re] Network Deconvolution
Author(s):Obadage, Rochana R. and Thennakoon, Kumushini and Rajtmajer, Sarah M. and Wu, Jian
Journal:ReScience C
Year:2025
Month:apr
Volume:10
Issue:1
Number:#4
DOI:10.5281/zenodo.15321683
Code URL:https://github.com/lamps-lab/rep-network-deconvolution
Code DOI:-
Data URL:https://www.kaggle.com/c/imagenet-object-localization-challenge/data
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Review URL:https://github.com/ReScience/submissions/issues/89
Cite as:Obadage, R.R., Thennakoon, K., Rajtmajer, S.M., and Wu, J. 2025. [Re] Network Deconvolution. ReScience C 10, 1, #4.
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Omeragić, E. and Đuranović, V. 2023. [Re] G-Mixup: Graph Data Augmentation for Graph Classification. ReScience C 9, 2, #1.

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Title:[Re] G-Mixup: Graph Data Augmentation for Graph Classification
Author(s):Omeragić, Ermin and Đuranović, Vuk
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#1
DOI:10.5281/zenodo.8173650
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Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=XxUIomN-ndH
Cite as:Omeragić, E. and Đuranović, V. 2023. [Re] G-Mixup: Graph Data Augmentation for Graph Classification. ReScience C 9, 2, #1.
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P, J.J. and Sardana, A. 2021. [Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings. ReScience C 7, 2, #15.

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Article (PDF):https://zenodo.org/record/4834942/files/article.pdf
Title:[Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
Author(s):P, Jishnu Jaykumar and Sardana, Ashish
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
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DOI:10.5281/zenodo.4834942
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Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=VFAwCMdWY7
Cite as:P, J.J. and Sardana, A. 2021. [Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings. ReScience C 7, 2, #15.
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Panigrahi, S.S. and Patnaik, S. 2022. [Re] Value Alignment Verification. ReScience C 8, 2, #31.

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Article (PDF):https://zenodo.org/record/6574687/files/article.pdf
Title:[Re] Value Alignment Verification
Author(s):Panigrahi, Siba Smarak and Patnaik, Sohan
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#31
DOI:10.5281/zenodo.6574687
Code URL:https://github.com/AIExL/vav_rc2021
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=BFLM3nMmhCt
Cite as:Panigrahi, S.S. and Patnaik, S. 2022. [Re] Value Alignment Verification. ReScience C 8, 2, #31.
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Pantalé, O. 2020. [Rp] Parallelization of an object-oriented FEM dynamics code. ReScience C 6, 1, #8.

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Article (PDF):https://zenodo.org/record/3901241
Title:[Rp] Parallelization of an object-oriented FEM dynamics code
Author(s):Pantalé, Olivier
Journal:ReScience C
Year:2020
Month:jun
Volume:6
Issue:1
Number:#8
DOI:10.5281/zenodo.3901241
Code URL:https://github.com/pantale/ReDynELA
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/19
Cite as:Pantalé, O. 2020. [Rp] Parallelization of an object-oriented FEM dynamics code. ReScience C 6, 1, #8.
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Pantea, L. and Blahovici, A. 2023. [Re] CrossWalk: Fairness-enhanced Node Representation Learning. ReScience C 9, 2, #39.

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Article (PDF):https://zenodo.org/record/8173749/files/article.pdf
Title:[Re] CrossWalk: Fairness-enhanced Node Representation Learning
Author(s):Pantea, Luca and Blahovici, Andrei
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#39
DOI:10.5281/zenodo.8173749
Code URL:https://github.com/Dawlau/FACT-AI
Code DOI:10.5281/zenodo.7932857
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=tpk45Zll8eh
Cite as:Pantea, L. and Blahovici, A. 2023. [Re] CrossWalk: Fairness-enhanced Node Representation Learning. ReScience C 9, 2, #39.
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Papp, G., Wagenbach, J., Vries, L.J. de, and Mather, N. 2023. [Re] Reproducibility study of ”Label-Free Explainability for Unsupervised Models.” ReScience C 9, 2, #24.

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Title:[Re] Reproducibility study of ”Label-Free Explainability for Unsupervised Models”
Author(s):Papp, Gergely and Wagenbach, Julius and de Vries, Laurens Jans and Mather, Niklas
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#24
DOI:10.5281/zenodo.8173711
Code URL:https://github.com/jwagenbach/FACT/
Code DOI:10.5281/zenodo.7895731
Data URL:-
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Review URL:https://openreview.net/forum?id=n2qXFXiMsAM
Cite as:Papp, G., Wagenbach, J., Vries, L.J. de, and Mather, N. 2023. [Re] Reproducibility study of ”Label-Free Explainability for Unsupervised Models.” ReScience C 9, 2, #24.
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Pariza, V., Pal, A., Pawar, M., and Faber, Q.S. 2023. [Re] Reproducibility Study of “Label-Free Explainability for Unsupervised Models.” ReScience C 9, 2, #11.

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Article (PDF):https://zenodo.org/record/8173674/files/article.pdf
Title:[Re] Reproducibility Study of “Label-Free Explainability for Unsupervised Models”
Author(s):Pariza, Valentinos and Pal, Avik and Pawar, Madhura and Faber, Quim Serra
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#11
DOI:10.5281/zenodo.8173674
Code URL:https://github.com/valentinosPariza/Re-Label-Free-XAI
Code DOI:-
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Data DOI:-
Review URL:https://openreview.net/forum?id=qP34dvJpHd
Cite as:Pariza, V., Pal, A., Pawar, M., and Faber, Q.S. 2023. [Re] Reproducibility Study of “Label-Free Explainability for Unsupervised Models.” ReScience C 9, 2, #11.
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Paul, T.E. and Bourdenx, M. 2021. [Re] Spread of alpha-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis. ReScience C 7, 1, #8.

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Article (PDF):https://zenodo.org/record/5379631/files/article.pdf
Title:[Re] Spread of alpha-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis
Author(s):Paul, Thomas E. and Bourdenx, Mathieu
Journal:ReScience C
Year:2021
Month:sep
Volume:7
Issue:1
Number:#8
DOI:10.5281/zenodo.5379631
Code URL:https://github.com/MathieuBo/PathoSpreading
Code DOI:-
Data URL:https://github.com/MathieuBo/PathoSpreading
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Review URL:https://github.com/ReScience/submissions/issues/54
Cite as:Paul, T.E. and Bourdenx, M. 2021. [Re] Spread of alpha-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis. ReScience C 7, 1, #8.
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Perazzo, D., Castro, D.G.N.S., Velho, L., and Figueiredo, L.H. de. 2026. [Re] Curve-Fitting with Piecewise Parametric Cubics. ReScience C 11, 1, #1.

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Title:[Re] Curve-Fitting with Piecewise Parametric Cubics
Author(s):Perazzo, Daniel and Castro, Davi Guimarães Nunes Sena and Velho, Luiz and de Figueiredo, Luiz Henrique
Journal:ReScience C
Year:2026
Month:jan
Volume:11
Issue:1
Number:#1
DOI:10.5281/zenodo.18400484
Code URL:https://github.com/danperazzo/plass_reproduction
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/93
Cite as:Perazzo, D., Castro, D.G.N.S., Velho, L., and Figueiredo, L.H. de. 2026. [Re] Curve-Fitting with Piecewise Parametric Cubics. ReScience C 11, 1, #1.
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Petchey, O., Plebani, M., and Pennekamp, F. 2016. [Re] Chaos in a long-term experiment with a plankton community. ReScience 2, 1, #3.

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Article (PDF):https://github.com/ReScience-Archives/Petchey-2016/raw/master/article/article.pdf
Title:[Re] Chaos in a long-term experiment with a plankton community
Author(s):Petchey, Owen and Plebani, Marco and Pennekamp, Frank
Journal:ReScience
Year:2016
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Number:#3
DOI:10.5281/zenodo.50213
Code URL:https://github.com/ReScience-Archives/Petchey-Plebani-Pennekamp-2016
Code DOI:10.5281/zenodo.50213
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/15
Cite as:Petchey, O., Plebani, M., and Pennekamp, F. 2016. [Re] Chaos in a long-term experiment with a plankton community. ReScience 2, 1, #3.
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Petcu, R., Praat, P., Wijnen, J., and Rerres, M. 2022. [Re] Replication Study of "Fairness and Bias in Online Selection". ReScience C 8, 2, #32.

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Article (PDF):https://zenodo.org/record/6574689/files/article.pdf
Title:[Re] Replication Study of "Fairness and Bias in Online Selection"
Author(s):Petcu, Roxana and Praat, Pim and Wijnen, Jeroen and Rerres, Manolis
Journal:ReScience C
Year:2022
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Volume:8
Issue:2
Number:#32
DOI:10.5281/zenodo.6574689
Code URL:https://github.com/pimpraat/FACT-Ai
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=S9gs3MmhAY
Cite as:Petcu, R., Praat, P., Wijnen, J., and Rerres, M. 2022. [Re] Replication Study of "Fairness and Bias in Online Selection". ReScience C 8, 2, #32.
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Peters, N., Crosbie, J., Hull, R. vant́, and Strampel, M. 2022. [¬Re] Reproducing ’Fair Selective Classification via Sufficiency.’ None 8, 2, #33.

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Article (PDF):https://zenodo.org/record/6574691/files/article.pdf
Title:[¬Re] Reproducing ’Fair Selective Classification via Sufficiency’
Author(s):Peters, Nils and Crosbie, Joy and vant́ Hull, Rachel and Strampel, Marius
Journal:None
Year:2022
Month:may
Volume:8
Issue:2
Number:#33
DOI:10.5281/zenodo.6574691
Code URL:https://github.com/MLRC2022FSCS/FSCS
Code DOI:10.5281/zenodo.6479342
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=r9Leh2M7hCt
Cite as:Peters, N., Crosbie, J., Hull, R. vant́, and Strampel, M. 2022. [¬Re] Reproducing ’Fair Selective Classification via Sufficiency.’ None 8, 2, #33.
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Picoche, C., Young, W.R., and Barraquand, F. 2022. [Re] Reproductive pair correlations and the clustering of organisms. ReScience C 8, 1, #3.

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Article (PDF):https://zenodo.org/record/6546488/files/article.pdf
Title:[Re] Reproductive pair correlations and the clustering of organisms
Author(s):Picoche, Coralie and Young, William R. and Barraquand, Frederic
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:1
Number:#3
DOI:10.5281/zenodo.6546488
Code URL:https://github.com/CoraliePicoche/brownian_bug_fluid/tree/main/code
Code DOI:10.5281/zenodo.6546471
Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/58
Cite as:Picoche, C., Young, W.R., and Barraquand, F. 2022. [Re] Reproductive pair correlations and the clustering of organisms. ReScience C 8, 1, #3.
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Pineau, J., Sinha, K., Fried, G., Ke, R.N., and Larochelle, H. 2019. ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #5.

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Article (PDF):https://zenodo.org/record/3158244/files/article.pdf
Title:ICLR Reproducibility Challenge 2019
Author(s):Pineau, Joelle and Sinha, Koustuv and Fried, Genevieve and Ke, Rosemary Nan and Larochelle, Hugo
Journal:ReScience C
Year:2019
Month:may
Volume:5
Issue:2
Number:#5
DOI:10.5281/zenodo.3158244
Code URL:-
Code DOI:-
Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/5
Cite as:Pineau, J., Sinha, K., Fried, G., Ke, R.N., and Larochelle, H. 2019. ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #5.
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Ranjan, R., Bhakta, H., Jha, A., and Maheshwari, P. 2022. [Re] Differentiable Spatial Planning using Transformers. ReScience C 8, 2, #34.

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Article (PDF):https://zenodo.org/record/6574693/files/article.pdf
Title:[Re] Differentiable Spatial Planning using Transformers
Author(s):Ranjan, Rohit and Bhakta, Himadri and Jha, Animesh and Maheshwari, Parv
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#34
DOI:10.5281/zenodo.6574693
Code URL:https://github.com/sirmisscriesalot/Differentiable-Spatial-Planning-using-Transformers
Code DOI:10.5281/zenodo.6475614
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=HFUI1pfQnCF
Cite as:Ranjan, R., Bhakta, H., Jha, A., and Maheshwari, P. 2022. [Re] Differentiable Spatial Planning using Transformers. ReScience C 8, 2, #34.
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Reijnaers, D.J.W., Pavert, D.B. van de, Scheuer, G., and Huang, L. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #16.

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Article (PDF):https://zenodo.org/record/4835056/files/article.pdf
Title:[Re] Explaining Groups of Points in Low-Dimensional Representations
Author(s):Reijnaers, Damiaan J. W. and van de Pavert, Daniël B. and Scheuer, Giguru and Huang, Liang
Journal:ReScience C
Year:2021
Month:may
Volume:7
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Number:#16
DOI:10.5281/zenodo.4835056
Code URL:https://github.com/damiaanr/fact-ai
Code DOI:10.5281/zenodo.4686025
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=hq3TxQK5cox
Cite as:Reijnaers, D.J.W., Pavert, D.B. van de, Scheuer, G., and Huang, L. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #16.
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Reynes, M. and Aussel, A. 2025. [Re] Model of thalamocortical slow-wave sleep oscillations and transitions to activated states. ReScience C 10, 1, #5.

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Article (PDF):https://zenodo.org/record/16529268/files/article.pdf
Title:[Re] Model of thalamocortical slow-wave sleep oscillations and transitions to activated states
Author(s):Reynes, Mathilde and Aussel, Amélie
Journal:ReScience C
Year:2025
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Code URL:https://github.com/Mathilde-Reynes/ReynesAussel2024.git
Code DOI:-
Data URL:https://doi.org/10.5281/zenodo.13376370
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Review URL:https://github.com/ReScience/submissions/issues/87
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Robert, C.H. 2020. [Rp] Reproducibility report: Estimating friction coefficients of mixed globular/chain molecules, such as protein/DNA complexes. [Biophys J 69, 840-848 (1995)]. ReScience C 6, 1, #4.

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Article (PDF):https://zenodo.org/record/3886412/files/article.pdf
Title:[Rp] Reproducibility report: Estimating friction coefficients of mixed globular/chain molecules, such as protein/DNA complexes. [Biophys J 69, 840-848 (1995)]
Author(s):Robert, Charles H.
Journal:ReScience C
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Cite as:Robert, C.H. 2020. [Rp] Reproducibility report: Estimating friction coefficients of mixed globular/chain molecules, such as protein/DNA complexes. [Biophys J 69, 840-848 (1995)]. ReScience C 6, 1, #4.
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Rougier, N.P. 2020. [Rp] LOUPE. ReScience C 6, 1, #3.

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Article (PDF):https://zenodo.org/record/3886628/files/article.pdf
Title:[Rp] LOUPE
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Journal:ReScience C
Year:2020
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DOI:10.5281/zenodo.3886628
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Roukema, B.F. 2020. [¬Rp] Reproducibility of ’Poincaré dodecahedral space parameter estimates.’ ReScience C 6, 1, #11.

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Article (PDF):https://zenodo.org/record/3943750/files/Roukema_ReSciC2020.pdf
Title:[¬Rp] Reproducibility of ’Poincaré dodecahedral space parameter estimates’
Author(s):Roukema, Boudewijn F.
Journal:ReScience C
Year:2020
Month:jul
Volume:6
Issue:1
Number:#11
DOI:10.5281/zenodo.3956058
Code URL:https://codeberg.org/boud/0807.4260
Code DOI:-
Data URL:https://lambda.gsfc.nasa.gov/data/map/dr3/dfp/wmap_ilc_5yr_v3.fits
Data DOI:-
Review URL:https://github.com/ReScience/submissions/issues/41
Cite as:Roukema, B.F. 2020. [¬Rp] Reproducibility of ’Poincaré dodecahedral space parameter estimates.’ ReScience C 6, 1, #11.
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Rucks, N., Uelwer, T., and Harmeling, S. 2022. [Re] Solving Phase Retrieval With a Learned Reference. ReScience C 8, 2, #35.

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Article (PDF):https://zenodo.org/record/6574695/files/article.pdf
Title:[Re] Solving Phase Retrieval With a Learned Reference
Author(s):Rucks, Nick and Uelwer, Tobias and Harmeling, Stefan
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#35
DOI:10.5281/zenodo.6574695
Code URL:https://github.com/tuelwer/machine-learning-reproducibility-challenge-2021
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=rlWzUnM72RF
Cite as:Rucks, N., Uelwer, T., and Harmeling, S. 2022. [Re] Solving Phase Retrieval With a Learned Reference. ReScience C 8, 2, #35.
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Sankar, R., Thou, N., Rougier, N.P., and Leblois, A. 2021. [Re] A Reservoir Computing Model of Reward-Modulated Motor Learning and Automaticity. ReScience C 7, 1, #11.

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Article (PDF):https://zenodo.org/record/5718075/files/article.pdf
Title:[Re] A Reservoir Computing Model of Reward-Modulated Motor Learning and Automaticity
Author(s):Sankar, Remya and Thou, Nicolas and Rougier, Nicolas P. and Leblois, Arthur
Journal:ReScience C
Year:2021
Month:nov
Volume:7
Issue:1
Number:#11
DOI:10.5281/zenodo.5718075
Code URL:https://github.com/rsankar9/Reimplementation-SUPERTREX/releases/tag/v3.0
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Review URL:https://github.com/ReScience/submissions/issues/50
Cite as:Sankar, R., Thou, N., Rougier, N.P., and Leblois, A. 2021. [Re] A Reservoir Computing Model of Reward-Modulated Motor Learning and Automaticity. ReScience C 7, 1, #11.
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Sant’Anna, G.B. de and Costa, M.F. 2022. [Re] A Multi-Functional Synthetic Gene Network. ReScience C 8, 1, #5.

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Title:[Re] A Multi-Functional Synthetic Gene Network
Author(s):de Sant’Anna, Gabriel Baiocchi and Costa, Mateus Favarin
Journal:ReScience C
Year:2022
Month:jul
Volume:8
Issue:1
Number:#5
DOI:10.5281/zenodo.6801765
Code URL:https://github.com/baioc/re-multif
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/13
Cite as:Sant’Anna, G.B. de and Costa, M.F. 2022. [Re] A Multi-Functional Synthetic Gene Network. ReScience C 8, 1, #5.
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Schneider, M. and Körner, M. 2021. [Re] Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention. ReScience C 7, 2, #19.

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Article (PDF):https://zenodo.org/record/4835356/files/article.pdf
Title:[Re] Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention
Author(s):Schneider, Maja and Körner, Marco
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#19
DOI:10.5281/zenodo.4835356
Code URL:https://github.com/maja601/pytorch-psetae
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Data URL:http://www.eurocrops.tum.de/
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Cite as:Schneider, M. and Körner, M. 2021. [Re] Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention. ReScience C 7, 2, #19.
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Sen, R., Sinha, S., Jha, A., and Maheshwari, P. 2022. [Re] Reproducibility Report: Contrastive Learning of Socially-aware Motion Representations. ReScience C 8, 2, #36.

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Article (PDF):https://zenodo.org/record/6574697/files/article.pdf
Title:[Re] Reproducibility Report: Contrastive Learning of Socially-aware Motion Representations
Author(s):Sen, Roopsa and Sinha, Sidharth and Jha, Animesh and Maheshwari, Parv
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#36
DOI:10.5281/zenodo.6574697
Code URL:https://github.com/RoopsaSen/social-nce-trajectron-plus-plus
Code DOI:10.5281/zenodo.6511007
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=SIQEl6f7h0Y
Cite as:Sen, R., Sinha, S., Jha, A., and Maheshwari, P. 2022. [Re] Reproducibility Report: Contrastive Learning of Socially-aware Motion Representations. ReScience C 8, 2, #36.
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Sheverdin, A., Knijff, A., Corten, N., and Lange, G. 2021. [Re] Reproducibility report of "Interpretable Complex-Valued Neural Networks for Privacy Protection". ReScience C 7, 2, #20.

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Article (PDF):https://zenodo.org/record/4835431/files/article.pdf
Title:[Re] Reproducibility report of "Interpretable Complex-Valued Neural Networks for Privacy Protection"
Author(s):Sheverdin, Arsen and Knijff, Alko and Corten, Noud and Lange, Georg
Journal:ReScience C
Year:2021
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Volume:7
Issue:2
Number:#20
DOI:10.5281/zenodo.4835431
Code URL:https://github.com/GANA-FACT-AI/gana-fact-ai
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Review URL:https://openreview.net/forum?id=P30M7d9DyXw
Cite as:Sheverdin, A., Knijff, A., Corten, N., and Lange, G. 2021. [Re] Reproducibility report of "Interpretable Complex-Valued Neural Networks for Privacy Protection". ReScience C 7, 2, #20.
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Shukla, A., Roy, S., Chawla, Y., et al. 2022. [Re] From goals, waypoints and paths to longterm human trajectory forecasting. ReScience C 8, 2, #37.

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Article (PDF):https://zenodo.org/record/6574699/files/article.pdf
Title:[Re] From goals, waypoints and paths to longterm human trajectory forecasting
Author(s):Shukla, Abhishek and Roy, Sourya and Chawla, Yogesh and Amalanshu, Avi and Pandey, Shubhendu and Agrawal, Rudransh and Uppal, Aditya and N, Viswesh and Mondal, Pradipto and Dasgupta, Anubhab and Chakravarty, Debashis
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#37
DOI:10.5281/zenodo.6574699
Code URL:https://github.com/Viswesh-N/MLRC-2021
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=HV2zgpM7n0F
Cite as:Shukla, A., Roy, S., Chawla, Y., et al. 2022. [Re] From goals, waypoints and paths to longterm human trajectory forecasting. ReScience C 8, 2, #37.
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Shulev, V., Verhagen, P., Wang, S., and Zhuge, J. 2022. [Re] Replication Study of DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks. ReScience C 8, 2, #43.

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Article (PDF):https://zenodo.org/record/6574711/files/article.pdf
Title:[Re] Replication Study of DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
Author(s):Shulev, Velizar and Verhagen, Paul and Wang, Shuai and Zhuge, Jennifer
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#43
DOI:10.5281/zenodo.6574711
Code URL:https://github.com/ShuaiWang97/UvA_FACT2022
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Review URL:https://openreview.net/forum?id=SVx46hzmhRK
Cite as:Shulev, V., Verhagen, P., Wang, S., and Zhuge, J. 2022. [Re] Replication Study of DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks. ReScience C 8, 2, #43.
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Silberbauer, M. 2020. Re ReScience challenge: Geographical Trends in the Water Chemistry of Wetlands in the South-Western Cape Province, South Africas. ReScience C 6, 1, #13.

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Article (PDF):https://zenodo.org/record/3996198/files/article.pdf
Title:Re ReScience challenge: Geographical Trends in the Water Chemistry of Wetlands in the South-Western Cape Province, South Africas
Author(s):Silberbauer, Michael
Journal:ReScience C
Year:2020
Month:aug
Volume:6
Issue:1
Number:#13
DOI:10.5281/zenodo.3996198
Code URL:-
Code DOI:-
Data URL:http://www.riv.co.za/wv/data/CHEMDATA.DAT
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Review URL:https://github.com/ReScience/submissions/issues/25
Cite as:Silberbauer, M. 2020. Re ReScience challenge: Geographical Trends in the Water Chemistry of Wetlands in the South-Western Cape Province, South Africas. ReScience C 6, 1, #13.
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Simoncini, W., Gogou, I., Lopes, M.F., and Kremer, R. 2023. [Re] Reproducibility Study of ”Focus On The Common Good: Group Distributional Robustness Follows.” ReScience C 9, 2, #23.

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Article (PDF):https://zenodo.org/record/8173707/files/article.pdf
Title:[Re] Reproducibility Study of ”Focus On The Common Good: Group Distributional Robustness Follows”
Author(s):Simoncini, Walter and Gogou, Ioanna and Lopes, Marta Freixo and Kremer, Ron
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#23
DOI:10.5281/zenodo.8173707
Code URL:https://github.com/WalterSimoncini/CGD-Reproduction
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Data DOI:-
Review URL:https://openreview.net/forum?id=ye8PftiQLQ
Cite as:Simoncini, W., Gogou, I., Lopes, M.F., and Kremer, R. 2023. [Re] Reproducibility Study of ”Focus On The Common Good: Group Distributional Robustness Follows.” ReScience C 9, 2, #23.
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Singh, A. and Bay, A. 2020. [Re] Improved Calibration and Predictive Uncertainty for Deep Neural Networks. ReScience C 6, 2, #10.

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Title:[Re] Improved Calibration and Predictive Uncertainty for Deep Neural Networks
Author(s):Singh, Aditya and Bay, Alessandro
Journal:ReScience C
Year:2020
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Volume:6
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DOI:10.5281/zenodo.3818605
Code URL:https://github.com/MacroMayhem/OnMixup
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Review URL:https://openreview.net/forum?id=JhZOkalsiI
Cite as:Singh, A. and Bay, A. 2020. [Re] Improved Calibration and Predictive Uncertainty for Deep Neural Networks. ReScience C 6, 2, #10.
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Sinha, K., Pineau, J., Forde, J., Ke, R.N., and Larochelle, H. 2020. NeurIPS 2019 Reproducibility Challenge. ReScience C 6, 2, #11.

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Article (PDF):https://zenodo.org/record/3818627/files/article.pdf
Title:NeurIPS 2019 Reproducibility Challenge
Author(s):Sinha, Koustuv and Pineau, Joelle and Forde, Jessica and Ke, Rosemary Nan and Larochelle, Hugo
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:2
Number:#11
DOI:10.5281/zenodo.3818627
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Data DOI:-
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Cite as:Sinha, K., Pineau, J., Forde, J., Ke, R.N., and Larochelle, H. 2020. NeurIPS 2019 Reproducibility Challenge. ReScience C 6, 2, #11.
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Sinha, K., Dodge, J., Luccioni, S., Forde, J.Z., Stojnic, R., and Pineau, J. 2021. ML Reproducibility Challenge 2020. ReScience C 7, 2, #1.

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Title:ML Reproducibility Challenge 2020
Author(s):Sinha, Koustuv and Dodge, Jesse and Luccioni, Sasha and Forde, Jessica Zosa and Stojnic, Robert and Pineau, Joelle
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#1
DOI:10.5281/zenodo.4833117
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Data DOI:-
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Cite as:Sinha, K., Dodge, J., Luccioni, S., Forde, J.Z., Stojnic, R., and Pineau, J. 2021. ML Reproducibility Challenge 2020. ReScience C 7, 2, #1.
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Sinha, K., Dodge, J., Luccioni, S., et al. 2022. ML Reproducibility Challenge 2021. ReScience C 8, 2, #48.

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Article (PDF):https://zenodo.org/record/6574723/files/article.pdf
Title:ML Reproducibility Challenge 2021
Author(s):Sinha, Koustuv and Dodge, Jesse and Luccioni, Sasha and Forde, Jessica Zosa and Raparthy, Sharath Chandra and Pineau, Joelle and Stojnic, Robert
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#48
DOI:10.5281/zenodo.6574723
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Cite as:Sinha, K., Dodge, J., Luccioni, S., et al. 2022. ML Reproducibility Challenge 2021. ReScience C 8, 2, #48.
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Sinha, K., Bleeker, M., Bhargav, S., et al. 2023. ML Reproducibility Challenge 2022. ReScience C 9, 2, #46.

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Article (PDF):https://zenodo.org/record/8200058/files/article.pdf
Title:ML Reproducibility Challenge 2022
Author(s):Sinha, Koustuv and Bleeker, Maurits and Bhargav, Samarth and Forde, Jessica Zosa and Raparthy, Sharath Chandra and Dodge, Jesse and Pineau, Joelle and Stojnic, Robert
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#46
DOI:10.5281/zenodo.8200058
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Špendl, M. and Pirc, K. 2023. [Re] Easy Bayesian Transfer Learning with Informative Priors. ReScience C 9, 2, #9.

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Title:[Re] Easy Bayesian Transfer Learning with Informative Priors
Author(s):Špendl, Martin and Pirc, Klementina
Journal:ReScience C
Year:2023
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Volume:9
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DOI:10.5281/zenodo.8173668
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Cite as:Špendl, M. and Pirc, K. 2023. [Re] Easy Bayesian Transfer Learning with Informative Priors. ReScience C 9, 2, #9.
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Stachelek, J. 2016. [Re] Least-cost modelling on irregular landscape graphs. ReScience 2, 1, #2.

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Stephen, K. and Menon, V. 2021. [Re] Learning Memory Guided Normality for Anomaly Detection. ReScience C 7, 2, #11.

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Journal:ReScience C
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Review URL:https://openreview.net/forum?id=vvLWTXkJ2Zv
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Stropnik, V. and Oražem, M. 2022. [Re] Graph Edit Networks. ReScience C 8, 2, #38.

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Title:[Re] Graph Edit Networks
Author(s):Stropnik, Vid and Oražem, Maruša
Journal:ReScience C
Year:2022
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Volume:8
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DOI:10.5281/zenodo.6574701
Code URL:https://github.com/MarusaOrazem/reproducibility_challenge
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Sukhoy, V. and Stoytchev, A. 2019. Eliminating the Variability of Cross-Validation Results with LIBLINEAR due to Randomization and Parallelization. ReScience C 5, 3, #1.

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Article (PDF):https://zenodo.org/record/3528175/files/article.pdf
Title:Eliminating the Variability of Cross-Validation Results with LIBLINEAR due to Randomization and Parallelization
Author(s):Sukhoy, Vladimir and Stoytchev, Alexander
Journal:ReScience C
Year:2019
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DOI:10.5281/zenodo.3528175
Code URL:https://github.com/sukhoy/cvrep
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Review URL:https://github.com/ReScience/submissions/issues/6
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Sun, K., Williams, A., and Hupkes, D. 2023. [Re] A Replication Study of Compositional Generalization Works on Semantic Parsing. ReScience C 9, 2, #44.

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Author(s):Sun, Kaiser and Williams, Adina and Hupkes, Dieuwke
Journal:ReScience C
Year:2023
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Volume:9
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DOI:10.5281/zenodo.8173759
Code URL:https://github.com/KaiserWhoLearns/CompGenRep_MLRC2022
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Review URL:https://openreview.net/forum?id=MF9uv95psps
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Sundar, V. and Dwaraknath, R.V. 2021. [Re] Rigging the Lottery: Making All Tickets Winners. ReScience C 7, 2, #21.

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Article (PDF):https://zenodo.org/record/4835564/files/article.pdf
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Author(s):Sundar, Varun and Dwaraknath, Rajat Vadiraj
Journal:ReScience C
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DOI:10.5281/zenodo.4835564
Code URL:https://github.com/varun19299/rigl-reproducibility
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Review URL:https://openreview.net/forum?id=riCIeP6LzEE
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Tafuro, M., Lombardo, A., Veljković, T.H., and Becker-Czarnetzki, L. 2022. [Re] Exacerbating Algorithmic Bias through Fairness Attacks. ReScience C 8, 2, #22.

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Title:[Re] Exacerbating Algorithmic Bias through Fairness Attacks
Author(s):Tafuro, Matteo and Lombardo, Andrea and Veljković, Tin Hadži and Becker-Czarnetzki, Lasse
Journal:ReScience C
Year:2022
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DOI:10.5281/zenodo.6574669
Code URL:https://github.com/imandrealombardo/FACT-AI
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Review URL:https://openreview.net/forum?id=H4lzChGmhCK
Cite as:Tafuro, M., Lombardo, A., Veljković, T.H., and Becker-Czarnetzki, L. 2022. [Re] Exacerbating Algorithmic Bias through Fairness Attacks. ReScience C 8, 2, #22.
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Taslimi, S., Foeng, L.C.A., Kayal, P., Patra, A.P., and Patra, A.P. 2023. [Re] Reproducibility Study of ’CartoonX: Cartoon Explanations of Image Classifiers.’ ReScience C 9, 2, #29.

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Title:[Re] Reproducibility Study of ’CartoonX: Cartoon Explanations of Image Classifiers’
Author(s):Taslimi, Sina and Foeng, Luke Chin A and Kayal, Pratik and Patra, Aditya Prakash and Patra, Aditya Prakash
Journal:ReScience C
Year:2023
Month:jul
Volume:9
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Number:#29
DOI:10.5281/zenodo.8173721
Code URL:https://github.com/KAISER1997/FACTAI_CARTOONX_Reproduce
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Cite as:Taslimi, S., Foeng, L.C.A., Kayal, P., Patra, A.P., and Patra, A.P. 2023. [Re] Reproducibility Study of ’CartoonX: Cartoon Explanations of Image Classifiers.’ ReScience C 9, 2, #29.
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Teule, T., Reints, N., Gerges, C.A., and Baanders, P. 2021. [Re] Deep Fair Clustering for Visual Learning. ReScience C 7, 2, #4.

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Title:[Re] Deep Fair Clustering for Visual Learning
Author(s):Teule, Tobias and Reints, Nienke and Gerges, Chris Al and Baanders, Pauline
Journal:ReScience C
Year:2021
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Volume:7
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DOI:10.5281/zenodo.4833547
Code URL:https://github.com/topteulen/UVA-FACT
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Review URL:https://openreview.net/forum?id=DXVAJGohUKs
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Togt, J. van der, Tiyavorabun, L., Rosati, M., and Starace, G. 2022. [Re] Badder Seeds: Reproducing the Evaluation of Lexical Methods for Bias Measurement. ReScience C 8, 2, #40.

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Title:[Re] Badder Seeds: Reproducing the Evaluation of Lexical Methods for Bias Measurement
Author(s):van der Togt, Jille and Tiyavorabun, Lea and Rosati, Matteo and Starace, Giulio
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#40
DOI:10.5281/zenodo.6574705
Code URL:https://github.com/thesofakillers/badder-seeds
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Cite as:Togt, J. van der, Tiyavorabun, L., Rosati, M., and Starace, G. 2022. [Re] Badder Seeds: Reproducing the Evaluation of Lexical Methods for Bias Measurement. ReScience C 8, 2, #40.
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Torre-Ortiz, C. de la and Nioche, A. 2021. [Re] Neural Network Model of Memory Retrieval. ReScience C 6, 3, #8.

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Title:[Re] Neural Network Model of Memory Retrieval
Author(s):de la Torre-Ortiz, Carlos and Nioche, Aurélien
Journal:ReScience C
Year:2021
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DOI:10.5281/zenodo.4461767
Code URL:https://github.com/c-torre/replication-recanatesi-2015
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Trojer, Ž. 2022. [Re] Transparent Object Tracking Benchmark. ReScience C 8, 2, #41.

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Journal:ReScience C
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DOI:10.5281/zenodo.6574707
Code URL:https://github.com/trojerz/TOTB-reproducability
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Review URL:https://openreview.net/forum?id=HxZZV3MQ20Y
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Türk, M., Busser, L., Dijk, D. van, and Bosch, M.J.A. 2023. [Re] Exploring the Explainability of Bias in Image Captioning Models. ReScience C 9, 2, #21.

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Article (PDF):https://zenodo.org/record/8173703/files/article.pdf
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Journal:ReScience C
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Code URL:https://github.com/martentyrk/mlrc2022hirota
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Cite as:Türk, M., Busser, L., Dijk, D. van, and Bosch, M.J.A. 2023. [Re] Exploring the Explainability of Bias in Image Captioning Models. ReScience C 9, 2, #21.
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Upshall, M. and Shifman, A.R. 2020. [Re] Mathematical analysis of depolarization block mediated by slow inactivation of fast sodium channels in midbrain dopamine neurons. ReScience C 6, 3, #1.

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Article (PDF):https://zenodo.org/record/3842360/files/article.pdf
Title:[Re] Mathematical analysis of depolarization block mediated by slow inactivation of fast sodium channels in midbrain dopamine neurons
Author(s):Upshall, Mary and Shifman, Aaron R.
Journal:ReScience C
Year:2020
Month:may
Volume:6
Issue:3
Number:#1
DOI:10.5281/zenodo.3842360
Code URL:https://github.com/mupsh/ReScience_Qian_2014
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/9
Cite as:Upshall, M. and Shifman, A.R. 2020. [Re] Mathematical analysis of depolarization block mediated by slow inactivation of fast sodium channels in midbrain dopamine neurons. ReScience C 6, 3, #1.
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Varma, M. and Prabhu, N. 2021. [Re] On the Relationship between Self-Attention and Convolutional Layers. ReScience C 7, 1, #6.

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Article (PDF):https://zenodo.org/record/5217602/files/article.pdf
Title:[Re] On the Relationship between Self-Attention and Convolutional Layers
Author(s):Varma, Mukund and Prabhu, Nishant
Journal:ReScience C
Year:2021
Month:aug
Volume:7
Issue:1
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DOI:10.5281/zenodo.5217602
Code URL:https://github.com/NishantPrabhu/Self-Attention-and-Convolutions
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Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/53
Cite as:Varma, M. and Prabhu, N. 2021. [Re] On the Relationship between Self-Attention and Convolutional Layers. ReScience C 7, 1, #6.
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Verhoeven, I., Chen, X., Hu, Q., and Holubar, M. 2021. [Re] Replication Study of ’Generative causal explanations of black-box classifiers.’ ReScience C 7, 2, #23.

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Article (PDF):https://zenodo.org/record/4835600/files/article.pdf
Title:[Re] Replication Study of ’Generative causal explanations of black-box classifiers’
Author(s):Verhoeven, Ivo and Chen, Xinyi and Hu, Qingzhi and Holubar, Mario
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#23
DOI:10.5281/zenodo.4835600
Code URL:https://github.com/shin-ee-chen/UvA_FACT_2021
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Data URL:-
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Review URL:https://openreview.net/forum?id=Vqtf4kZg2j
Cite as:Verhoeven, I., Chen, X., Hu, Q., and Holubar, M. 2021. [Re] Replication Study of ’Generative causal explanations of black-box classifiers.’ ReScience C 7, 2, #23.
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Verma, R., Wagemans, J.J.O., Dahal, P., and Elfrink, A. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #24.

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Article (PDF):https://zenodo.org/record/4835602/files/article.pdf
Title:[Re] Explaining Groups of Points in Low-Dimensional Representations
Author(s):Verma, Rajeev and Wagemans, Jim J. O. and Dahal, Paras and Elfrink, Auke
Journal:ReScience C
Year:2021
Month:may
Volume:7
Issue:2
Number:#24
DOI:10.5281/zenodo.4835602
Code URL:https://github.com/elfrink1/FACT
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Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=cqAHExg2f
Cite as:Verma, R., Wagemans, J.J.O., Dahal, P., and Elfrink, A. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #24.
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Vleuten, N. van der, Radusinović, T., Akkerman, R., and Reksoprodjo, M. 2022. [Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace. None 8, 2, #42.

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Article (PDF):https://zenodo.org/record/6574709/files/article.pdf
Title:[Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Author(s):van der Vleuten, Noah and Radusinović, Tadija and Akkerman, Rick and Reksoprodjo, Meilina
Journal:None
Year:2022
Month:may
Volume:8
Issue:2
Number:#42
DOI:10.5281/zenodo.6574709
Code URL:https://github.com/NoahVl/Explaining-In-Style-Reproducibility-Study
Code DOI:10.5281/zenodo.6512392
Data URL:-
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Review URL:https://openreview.net/forum?id=SYUxyazQh0Y
Cite as:Vleuten, N. van der, Radusinović, T., Akkerman, R., and Reksoprodjo, M. 2022. [Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace. None 8, 2, #42.
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Wagner, S.D., Kurowski, Y.P., Holländer, L.M., and Uelwer, T. 2025. [Re] When Does Label Smoothing Help? ReScience C 10, 1, #1.

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Article (PDF):https://zenodo.org/records/14953654/files/article.pdf
Title:[Re] When Does Label Smoothing Help?
Author(s):Wagner, Sven Dominik and Kurowski, Yann Philipp and Holländer, Leonhard Moritz and Uelwer, Tobias
Journal:ReScience C
Year:2025
Month:feb
Volume:10
Issue:1
Number:#1
DOI:10.5281/zenodo.14953654
Code URL:https://github.com/sdwagner/re-labelsmoothing/
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Review URL:https://github.com/ReScience/submissions/issues/75
Cite as:Wagner, S.D., Kurowski, Y.P., Holländer, L.M., and Uelwer, T. 2025. [Re] When Does Label Smoothing Help? ReScience C 10, 1, #1.
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Wallrich, L. 2022. [Re] Groups of diverse problem-solvers outperform groups of highest-ability problem-solvers - most of the time. ReScience C 8, 1, #6.

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Article (PDF):https://zenodo.org/record/7484072/files/article.pdf
Title:[Re] Groups of diverse problem-solvers outperform groups of highest-ability problem-solvers - most of the time
Author(s):Wallrich, Lukas
Journal:ReScience C
Year:2022
Month:dec
Volume:8
Issue:1
Number:#6
DOI:10.5281/zenodo.7484072
Code URL:https://github.com/LukasWallrich/diversity_abm_replication
Code DOI:-
Data URL:-
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Review URL:https://github.com/ReScience/submissions/issues/61
Cite as:Wallrich, L. 2022. [Re] Groups of diverse problem-solvers outperform groups of highest-ability problem-solvers - most of the time. ReScience C 8, 1, #6.
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Warmerdam, A.T., Loerakker, L., Meijer, L., and Nissen, O. 2022. [Re] Privacy-preserving collaborative learning with automatic transformation search. ReScience C 8, 2, #44.

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Article (PDF):https://zenodo.org/record/6574713/files/article.pdf
Title:[Re] Privacy-preserving collaborative learning with automatic transformation search
Author(s):Warmerdam, Alfonso Taboada and Loerakker, Lodewijk and Meijer, Lucas and Nissen, Ole
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#44
DOI:10.5281/zenodo.6574713
Code URL:https://github.com/Linkerbrain/fact-ai-2021-project
Code DOI:10.5281/zenodo.6482966
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=S9Iepnz7hRY
Cite as:Warmerdam, A.T., Loerakker, L., Meijer, L., and Nissen, O. 2022. [Re] Privacy-preserving collaborative learning with automatic transformation search. ReScience C 8, 2, #44.
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Weinman, J. 2020. [Rp] Reproducing "Typographical Features for Scene Text Recognition". ReScience C 6, 1, #.

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Article (PDF):https://zenodo.org/record/4091742/files/article.pdf
Title:[Rp] Reproducing "Typographical Features for Scene Text Recognition"
Author(s):Weinman, Jerod
Journal:ReScience C
Year:2020
Month:oct
Volume:6
Issue:1
Number:#
DOI:10.5281/zenodo.4091742
Code URL:http://hdl.handle.net/11084/23333
Code DOI:11084/23333
Data URL:http://hdl.handle.net/11084/23336
Data DOI:11084/23336
Review URL:https://github.com/ReScience/submissions/issues/35
Cite as:Weinman, J. 2020. [Rp] Reproducing "Typographical Features for Scene Text Recognition". ReScience C 6, 1, #.
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Wilschut, R.I., Wiggers, T.P.A., Oort, R.S., and Orden, T.A. van. 2022. [Re] Robust Counterfactual Explanations on Graph Neural Networks. ReScience C 8, 2, #45.

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Article (PDF):https://zenodo.org/record/6574715/files/article.pdf
Title:[Re] Robust Counterfactual Explanations on Graph Neural Networks
Author(s):Wilschut, Romana Isabelle and Wiggers, Thomas Paul Alexandre and Oort, Roman Sebastiaan and van Orden, Thomas Arthur
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#45
DOI:10.5281/zenodo.6574715
Code URL:https://github.com/RomanOort/FACTAI
Code DOI:-
Data URL:-
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Review URL:https://openreview.net/forum?id=HWNgihGX20Y
Cite as:Wilschut, R.I., Wiggers, T.P.A., Oort, R.S., and Orden, T.A. van. 2022. [Re] Robust Counterfactual Explanations on Graph Neural Networks. ReScience C 8, 2, #45.
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Yılmaz, D., Kınlı, F., Özcan, B., and Kıraç, F. 2022. [Re] Lifting 2D StyleGAN for 3D-Aware Face Generation. ReScience C 8, 2, #46.

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Article (PDF):https://zenodo.org/record/6574719/files/article.pdf
Title:[Re] Lifting 2D StyleGAN for 3D-Aware Face Generation
Author(s):Yılmaz, Doğa and Kınlı, Furkan and Özcan, Barış and Kıraç, Furkan
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#46
DOI:10.5281/zenodo.6574719
Code URL:https://github.com/yilmazdoga/lifting-2d-stylegan-for-3d-aware-face-generation
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=BcNonfQ3RY
Cite as:Yılmaz, D., Kınlı, F., Özcan, B., and Kıraç, F. 2022. [Re] Lifting 2D StyleGAN for 3D-Aware Face Generation. ReScience C 8, 2, #46.
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Yuan, J. and Le-Phuoc, D. 2023. [Re] Hypergraph-Induced Semantic Tuplet Loss for Deep Metric Learning. ReScience C 9, 2, #8.

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Article (PDF):https://zenodo.org/record/8173666/files/article.pdf
Title:[Re] Hypergraph-Induced Semantic Tuplet Loss for Deep Metric Learning
Author(s):Yuan, Jicheng and Le-Phuoc, Danh
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#8
DOI:10.5281/zenodo.8173666
Code URL:https://github.com/jichengyuan/MLRC2022_HIST
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Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=JJQbk2hIQ5
Cite as:Yuan, J. and Le-Phuoc, D. 2023. [Re] Hypergraph-Induced Semantic Tuplet Loss for Deep Metric Learning. ReScience C 9, 2, #8.
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Zila, E., Gerbscheid, J., Sträter, L., and Kretschmar, K. 2023. [Re] On the reproducibility of "CrossWalk: Fairness-Enhanced Node Representation Learning". ReScience C 9, 2, #27.

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Article (PDF):https://zenodo.org/record/8173717/files/article.pdf
Title:[Re] On the reproducibility of "CrossWalk: Fairness-Enhanced Node Representation Learning"
Author(s):Zila, Eric and Gerbscheid, Jonathan and Sträter, Luc and Kretschmar, Kieron
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#27
DOI:10.5281/zenodo.8173717
Code URL:https://github.com/jonathan-gerb/crosswalk-reproduction
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=WnaVgRhlyT
Cite as:Zila, E., Gerbscheid, J., Sträter, L., and Kretschmar, K. 2023. [Re] On the reproducibility of "CrossWalk: Fairness-Enhanced Node Representation Learning". ReScience C 9, 2, #27.
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Žontar, L. 2023. [Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization. ReScience C 9, 2, #7.

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Article (PDF):https://zenodo.org/record/8173664/files/article.pdf
Title:[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
Author(s):Žontar, Luka
Journal:ReScience C
Year:2023
Month:jul
Volume:9
Issue:2
Number:#7
DOI:10.5281/zenodo.8173664
Code URL:https://github.com/lukazontar/RC2022-Bandit-Theory-and-Thompson-Sampling-Guided-Directed-Evolution-for-Sequence-Optimization
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Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=NE_x1dpz-Q
Cite as:Žontar, L. 2023. [Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization. ReScience C 9, 2, #7.
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Zrimšek, U. 2022. [Re] Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction. ReScience C 8, 2, #47.

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Article (PDF):https://zenodo.org/record/6574721/files/article.pdf
Title:[Re] Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction
Author(s):Zrimšek, Urša
Journal:ReScience C
Year:2022
Month:may
Volume:8
Issue:2
Number:#47
DOI:10.5281/zenodo.6574721
Code URL:https://github.com/zrimseku/Reproducibility-Challenge
Code DOI:10.5281/zenodo.6511807
Data URL:-
Data DOI:-
Review URL:https://openreview.net/forum?id=Hc8GOhfmhRF
Cite as:Zrimšek, U. 2022. [Re] Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction. ReScience C 8, 2, #47.
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+ +
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+ ReScience C +
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Bavard, S. and Théro, H. 2018. [Re] Adaptive properties of differential learning rates for positive and negative outcomes. ReScience 4, 1, #5.

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Article (PDF):https://github.com/ReScience-Archives/Bavard-Thero-2018/raw/master/article/Bavard-Thero-2018.pdf
Title:[Re] Adaptive properties of differential learning rates for positive and negative outcomes
Author(s):Bavard, Sophie and Théro, Héloïse
Journal:ReScience
Year:2018
Month:jun
Volume:4
Issue:1
Number:#5
DOI:10.5281/zenodo.1289889
Code URL:https://github.com/ReScience-Archives/Bavard-Thero-2018
Code DOI:10.5281/zenodo.1289889
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/47
Cite as:Bavard, S. and Théro, H. 2018. [Re] Adaptive properties of differential learning rates for positive and negative outcomes. ReScience 4, 1, #5.
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+ + + + + + + diff --git a/bibliography/caron_2019.html b/bibliography/caron_2019.html new file mode 100644 index 0000000..0701037 --- /dev/null +++ b/bibliography/caron_2019.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] Insect natural enemies as regulating factors + + + + + + + + + + + +
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Caron, D., Lessard, V., Wu, Q., and Poisot, T. 2019. [Re] Insect natural enemies as regulating factors. ReScience 5, 1, #1.

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Article (PDF):https://github.com/ReScience-Archives/Caron-Lessard-Wu-Poisot-2019/blob/master/article/Caron-Lessard-Wu-Poisot-2019.pdf
Title:[Re] Insect natural enemies as regulating factors
Author(s):Caron, Dominique and Lessard, Vincent and Wu, Qile and Poisot, Timothée
Journal:ReScience
Year:2019
Month:jan
Volume:5
Issue:1
Number:#1
DOI:10.5281/zenodo.2598793
Code URL:https://github.com/ReScience-Archives/Caron-Lessard-Wu-Poisot-2019
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/50
Cite as:Caron, D., Lessard, V., Wu, Q., and Poisot, T. 2019. [Re] Insect natural enemies as regulating factors. ReScience 5, 1, #1.
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+ + + + + + + diff --git a/bibliography/caze_2018.html b/bibliography/caze_2018.html new file mode 100644 index 0000000..fbae2ca --- /dev/null +++ b/bibliography/caze_2018.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] Non-additive coupling enables propagation of + synchronous spiking activity in purely random networks + + + + + + + + + + + +
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+ ReScience C +
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Cazé, R., Stimberg, M., and Girard, B. 2018. [Re] Non-additive coupling enables propagation of + synchronous spiking activity in purely random networks. ReScience 4, 1, #1.

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Article (PDF):https://github.com/ReScience-Archives/Caze-Stimberg-Girard-2018/blob/master/article/Caze_2018.pdf
Title:[Re] Non-additive coupling enables propagation of + synchronous spiking activity in purely random networks
Author(s):Cazé, Romain and Stimberg, Marcel and Girard, Benoît
Journal:ReScience
Year:2018
Month:may
Volume:4
Issue:1
Number:#1
DOI:10.5281/zenodo.1246659
Code URL:https://github.com/ReScience-Archives/Caze-Stimberg-Girard-2018/
Code DOI:10.5281/zenodo.1246659
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/45
Cite as:Cazé, R., Stimberg, M., and Girard, B. 2018. [Re] Non-additive coupling enables propagation of + synchronous spiking activity in purely random networks. ReScience 4, 1, #1.
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+ + + + + + + diff --git a/bibliography/detorakis_2016.html b/bibliography/detorakis_2016.html new file mode 100644 index 0000000..42a8dfd --- /dev/null +++ b/bibliography/detorakis_2016.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] Multiple dynamical modes of thalamic relay neurons: + rhythmic bursting and intermittent phase-locking + + + + + + + + + + + +
+ +
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+ ReScience C +
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Detorakis, G. 2016. [Re] Multiple dynamical modes of thalamic relay neurons: + rhythmic bursting and intermittent phase-locking. ReScience 2, 1, #4.

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Article (PDF):https://github.com/ReScience-Archives/Detorakis-2016/raw/master/article/detorakis-2016.pdf
Title:[Re] Multiple dynamical modes of thalamic relay neurons: + rhythmic bursting and intermittent phase-locking
Author(s):Detorakis, Georgios
Journal:ReScience
Year:2016
Month:sep
Volume:2
Issue:1
Number:#4
DOI:10.5281/zenodo.61697
Code URL:https://github.com/ReScience-Archives/Detorakis-2016.git
Code DOI:10.5281/zenodo.61697
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/17
Cite as:Detorakis, G. 2016. [Re] Multiple dynamical modes of thalamic relay neurons: + rhythmic bursting and intermittent phase-locking. ReScience 2, 1, #4.
+ + + + + +
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+ + + + + + + diff --git a/bibliography/detorakis_2017.html b/bibliography/detorakis_2017.html new file mode 100644 index 0000000..571baf7 --- /dev/null +++ b/bibliography/detorakis_2017.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors + + + + + + + + + + + +
+ +
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+ ReScience C +
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Detorakis, G. 2017. [Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors. ReScience 3, 1, #7.

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Article (PDF):https://github.com/ReScience-Archives/Detorakis-2017/blob/master/article/detorakis-2017.pdf
Title:[Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors
Author(s):Detorakis, Georgios
Journal:ReScience
Year:2017
Month:oct
Volume:3
Issue:1
Number:#7
DOI:10.5281/zenodo.1003214
Code URL:https://github.com/ReScience-Archives/Detorakis-2017
Code DOI:10.5281/zenodo.1003214
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/35
Cite as:Detorakis, G. 2017. [Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors. ReScience 3, 1, #7.
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+ + + + + + + diff --git a/bibliography/diem_2017.html b/bibliography/diem_2017.html new file mode 100644 index 0000000..f4c9d36 --- /dev/null +++ b/bibliography/diem_2017.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] A bidirectional model for communication in the neurovascular unit + + + + + + + + + + + +
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+ ReScience C +
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Diem, A.K. 2017. [Re] A bidirectional model for communication in the neurovascular unit. ReScience 3, 1, #9.

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Article (PDF):https://github.com/ReScience-Archives/Diem-2017/blob/master/article/Diem-2017.pdf
Title:[Re] A bidirectional model for communication in the neurovascular unit
Author(s):Diem, Alexandra K.
Journal:ReScience
Year:2017
Month:sep
Volume:3
Issue:1
Number:#9
DOI:10.5281/zenodo.890901
Code URL:https://github.com/ReScience-Archives/Diem-2017
Code DOI:10.5281/zenodo.890901
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/33
Cite as:Diem, A.K. 2017. [Re] A bidirectional model for communication in the neurovascular unit. ReScience 3, 1, #9.
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+ + + + + + + diff --git a/bibliography/hathway_2018.html b/bibliography/hathway_2018.html new file mode 100644 index 0000000..86874ff --- /dev/null +++ b/bibliography/hathway_2018.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains + + + + + + + + + + + +
+ +
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+ ReScience C +
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Hathway, P. and Goodman, D.F.M. 2018. [Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains. ReScience 4, 1, #6.

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Article (PDF):https://github.com/ReScience-Archives/Hathway-Goodman-2018/blob/master/article/Hathway-Goodman-2018.pdf
Title:[Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains
Author(s):Hathway, Pamela and Goodman, Dan F. M.
Journal:ReScience
Year:2018
Month:aug
Volume:4
Issue:1
Number:#6
DOI:10.5281/zenodo.1327348
Code URL:https://github.com/ReScience-Archives/Hathway-Goodman-2018
Code DOI:10.5281/zenodo.1327348
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/51
Cite as:Hathway, P. and Goodman, D.F.M. 2018. [Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains. ReScience 4, 1, #6.
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+ + + + + + + diff --git a/bibliography/henriques_2017.html b/bibliography/henriques_2017.html new file mode 100644 index 0000000..18b49cb --- /dev/null +++ b/bibliography/henriques_2017.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] Optimization of a free water elimination + two-compartment model for diffusion tensor imaging + + + + + + + + + + + +
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+ ReScience C +
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Henriques, R.N., Rokem, A., Garyfallidis, E., St-Jean, S., Peterson, E.T., and Correia, M.M. 2017. [Re] Optimization of a free water elimination + two-compartment model for diffusion tensor imaging. ReScience 3, 1, #2.

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Article (PDF):https://github.com/ReScience-Archives/Henriques-Rokem-Garyfallidis-St-Jean-Peterson-Correia-2017/raw/master/article/Henriques-Rokem-Garyfallidis-St-Jean-Peterson-Correia-2017.pdf
Title:[Re] Optimization of a free water elimination + two-compartment model for diffusion tensor imaging
Author(s):Henriques, Rafael Neto and Rokem, Ariel and Garyfallidis, Eleftherios and St-Jean, Samuel and Peterson, Eric Thomas and Correia, Marta Morgado
Journal:ReScience
Year:2017
Month:apr
Volume:3
Issue:1
Number:#2
DOI:10.5281/zenodo.495237
Code URL:https://github.com/ReScience-Archives/Henriques-Rokem-Garyfallidis-St-Jean-Peterson-Correia-2017
Code DOI:10.5281/zenodo.495237
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/26
Cite as:Henriques, R.N., Rokem, A., Garyfallidis, E., St-Jean, S., Peterson, E.T., and Correia, M.M. 2017. [Re] Optimization of a free water elimination + two-compartment model for diffusion tensor imaging. ReScience 3, 1, #2.
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+ +
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+ ReScience C +
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Masson, E.L. and Alexandre, F. 2016. [Re] How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks. ReScience 2, 1, #7.

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Article (PDF):https://github.com/ReScience-Archives/Le_Masson-Alexandre-2016/raw/master/article/Le_Masson-Alexandre-2016.pdf
Title:[Re] How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks
Author(s):Masson, Erwan Le and Alexandre, Frédéric
Journal:ReScience
Year:2016
Month:dec
Volume:2
Issue:1
Number:#7
DOI:10.5281/zenodo.200334
Code URL:https://github.com/ReScience-Archives/Le_Masson-Alexandre-2016
Code DOI:10.5281/zenodo.200334
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/21
Cite as:Masson, E.L. and Alexandre, F. 2016. [Re] How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks. ReScience 2, 1, #7.
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+ + + + + + + diff --git a/bibliography/maksimov_2016.html b/bibliography/maksimov_2016.html new file mode 100644 index 0000000..a5c884e --- /dev/null +++ b/bibliography/maksimov_2016.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model + + + + + + + + + + + +
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Maksimov, A., Albada, S.J. van, and Diesmann, M. 2016. [Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model. ReScience 2, 1, #6.

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Article (PDF):https://github.com/ReScience-Archives/Maksimov-Albada-Diesmann-2016/raw/master/article/maksimov-albada-diesmann-2016.pdf
Title:[Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model
Author(s):Maksimov, Andrei and van Albada, Sacha J. and Diesmann, Markus
Journal:ReScience
Year:2016
Month:oct
Volume:2
Issue:1
Number:#6
DOI:10.5281/zenodo.161526
Code URL:https://github.com/ReScience-Archives/Maksimov-Albada-Diesmann-2016
Code DOI:10.5281/zenodo.161526
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/18
Cite as:Maksimov, A., Albada, S.J. van, and Diesmann, M. 2016. [Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model. ReScience 2, 1, #6.
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+ + + + + + + diff --git a/bibliography/metzner_2017.html b/bibliography/metzner_2017.html new file mode 100644 index 0000000..c1047f2 --- /dev/null +++ b/bibliography/metzner_2017.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] Modeling GABA Alterations in Schizophrenia: A Link Between Impaired Inhibition and Gamma and Beta Auditory Entrainment + + + + + + + + + + + +
+ +
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+ ReScience C +
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Metzner, C. 2017. [Re] Modeling GABA Alterations in Schizophrenia: A Link Between Impaired Inhibition and Gamma and Beta Auditory Entrainment. ReScience 3, 1, #6.

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Article (PDF):https://github.com/ReScience-Archives/Metzner-2017/blob/1.0/article/Metzner-2017.pdf
Title:[Re] Modeling GABA Alterations in Schizophrenia: A Link Between Impaired Inhibition and Gamma and Beta Auditory Entrainment
Author(s):Metzner, Christoph
Journal:ReScience
Year:2017
Month:aug
Volume:3
Issue:1
Number:#6
DOI:10.5281/zenodo.854616
Code URL:https://github.com/ReScience-Archives/Metzner-2017/
Code DOI:10.5281/zenodo.854616
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/30
Cite as:Metzner, C. 2017. [Re] Modeling GABA Alterations in Schizophrenia: A Link Between Impaired Inhibition and Gamma and Beta Auditory Entrainment. ReScience 3, 1, #6.
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+ + + + + + + diff --git a/bibliography/mondeel_2018.html b/bibliography/mondeel_2018.html new file mode 100644 index 0000000..1fdce77 --- /dev/null +++ b/bibliography/mondeel_2018.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] Predicting metabolic biomarkers of human inborn errors + of metabolism + + + + + + + + + + + +
+ +
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+ ReScience C +
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Mondeel, T.D.G.A., Ogundipe, V., and Westerhoff, H.V. 2018. [Re] Predicting metabolic biomarkers of human inborn errors + of metabolism. ReScience 4, 1, #4.

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Article (PDF):https://github.com/ReScience-Archives/Mondeel-Ogundipe-Westerhoff-2018/blob/master/article/Mondeel_Ogundipe_Westerhoff-2017.pdf
Title:[Re] Predicting metabolic biomarkers of human inborn errors + of metabolism
Author(s):Mondeel, Thierry D.G.A. and Ogundipe, Vivian and Westerhoff, Hans V.
Journal:ReScience
Year:2018
Month:may
Volume:4
Issue:1
Number:#4
DOI:10.5281/zenodo.1254629
Code URL:https://github.com/ReScience-Archives/Mondeel-Ogundipe-Westerhoff-2018
Code DOI:10.5281/zenodo.1254629
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/41
Cite as:Mondeel, T.D.G.A., Ogundipe, V., and Westerhoff, H.V. 2018. [Re] Predicting metabolic biomarkers of human inborn errors + of metabolism. ReScience 4, 1, #4.
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+ + + + + + + diff --git a/bibliography/poisot_2018.html b/bibliography/poisot_2018.html new file mode 100644 index 0000000..c85a47f --- /dev/null +++ b/bibliography/poisot_2018.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] On the coexistence of specialists and generalists + + + + + + + + + + + +
+ +
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+ ReScience C +
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Poisot, T. 2018. [Re] On the coexistence of specialists and generalists. ReScience 4, 1, #7.

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Article (PDF):https://github.com/ReScience-Archives/Poisot-2018/blob/master/article/Poisot-2018.pdf
Title:[Re] On the coexistence of specialists and generalists
Author(s):Poisot, Timothée
Journal:ReScience
Year:2018
Month:aug
Volume:4
Issue:1
Number:#7
DOI:10.5281/zenodo.1402676
Code URL:https://github.com/ReScience-Archives/Poisot-2018
Code DOI:10.5281/zenodo.1402676
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/39
Cite as:Poisot, T. 2018. [Re] On the coexistence of specialists and generalists. ReScience 4, 1, #7.
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+ + + + + + + diff --git a/bibliography/rostami_2017.html b/bibliography/rostami_2017.html new file mode 100644 index 0000000..0d9f200 --- /dev/null +++ b/bibliography/rostami_2017.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] Spike Synchronization and Rate Modulation + Differentially Involved in Motor Cortical Function + + + + + + + + + + + +
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+ ReScience C +
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Rostami, V., Ito, J., Denker, M., and Grün, S. 2017. [Re] Spike Synchronization and Rate Modulation + Differentially Involved in Motor Cortical Function. ReScience 3, 1, #3.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Article (PDF):https://github.com/ReScience-Archives/Rostami-Ito-Denker-Gruen-2017/blob/master/article/Rostami-Ito-Denker-Gruen-2017.pdf
Title:[Re] Spike Synchronization and Rate Modulation + Differentially Involved in Motor Cortical Function
Author(s):Rostami, Vahid and Ito, Junji and Denker, Michael and Grün, Sonja
Journal:ReScience
Year:2017
Month:may
Volume:3
Issue:1
Number:#3
DOI:10.5281/zenodo.583814
Code URL:https://github.com/ReScience-Archives/Rostami-Ito-Denker-Gruen-2017
Code DOI:10.5281/zenodo.583814
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/24
Cite as:Rostami, V., Ito, J., Denker, M., and Grün, S. 2017. [Re] Spike Synchronization and Rate Modulation + Differentially Involved in Motor Cortical Function. ReScience 3, 1, #3.
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+ + + + + + + diff --git a/bibliography/rougier_2017.html b/bibliography/rougier_2017.html new file mode 100644 index 0000000..b9358fe --- /dev/null +++ b/bibliography/rougier_2017.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] Weighted Voronoi Stippling + + + + + + + + + + + +
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Rougier, N.P. 2017. [Re] Weighted Voronoi Stippling. ReScience 3, 1, #4.

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Article (PDF):https://github.com/ReScience-Archives/Rougier-2017/blob/master/article/Rougier-2017.pdf
Title:[Re] Weighted Voronoi Stippling
Author(s):Rougier, Nicolas P.
Journal:ReScience
Year:2017
Month:jun
Volume:3
Issue:1
Number:#4
DOI:10.5281/zenodo.802285
Code URL:https://github.com/ReScience-Archives/Rougier-2017
Code DOI:10.5281/zenodo.802285
Data URL:https://github.com/ReScience-Archives/Rougier-2017/tree/master/data
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/28
Cite as:Rougier, N.P. 2017. [Re] Weighted Voronoi Stippling. ReScience 3, 1, #4.
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+ + + + + + + diff --git a/bibliography/senden_2018.html b/bibliography/senden_2018.html new file mode 100644 index 0000000..344aa76 --- /dev/null +++ b/bibliography/senden_2018.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] A neural model of the saccade generator in the + reticular formation + + + + + + + + + + + +
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Senden, M., Schuecker, J., Hahne, J., Diesmann, M., and Goebel, R. 2018. [Re] A neural model of the saccade generator in the + reticular formation. ReScience 4, 1, #3.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Article (PDF):https://github.com/ReScience-Archives/Senden-Schuecker-Hahne-Diesmann-Goebel-2018/blob/master/article/senden-schuecker-hahne-diesmann-goebel-2018.pdf
Title:[Re] A neural model of the saccade generator in the + reticular formation
Author(s):Senden, Mario and Schuecker, Jannis and Hahne, Jan and Diesmann, Markus and Goebel, Rainer
Journal:ReScience
Year:2018
Month:may
Volume:4
Issue:1
Number:#3
DOI:10.5281/zenodo.1241004
Code URL:https://github.com/ReScience-Archives/Senden-Schuecker-Hahne-Diesmann-Goebel-2018
Code DOI:10.5281/zenodo.1241004
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/46
Cite as:Senden, M., Schuecker, J., Hahne, J., Diesmann, M., and Goebel, R. 2018. [Re] A neural model of the saccade generator in the + reticular formation. ReScience 4, 1, #3.
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+ + + + + + + diff --git a/bibliography/shifman_2017.html b/bibliography/shifman_2017.html new file mode 100644 index 0000000..a207211 --- /dev/null +++ b/bibliography/shifman_2017.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] Ionic Current Model of a Hypoglossal Motoneuron + + + + + + + + + + + +
+ +
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Shifman, A. 2017. [Re] Ionic Current Model of a Hypoglossal Motoneuron. ReScience 3, 1, #1.

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Article (PDF):https://github.com/ReScience-Archives/Shifman-2017/raw/master/article/shifman-2017.pdf
Title:[Re] Ionic Current Model of a Hypoglossal Motoneuron
Author(s):Shifman, Aaron
Journal:ReScience
Year:2017
Month:jan
Volume:3
Issue:1
Number:#1
DOI:10.5281/zenodo.254145
Code URL:https://github.com/ReScience-Archives/Shifman-2017
Code DOI:10.5281/zenodo.254145
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/22
Cite as:Shifman, A. 2017. [Re] Ionic Current Model of a Hypoglossal Motoneuron. ReScience 3, 1, #1.
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+ + + + + + + diff --git a/bibliography/shimoura_2018.html b/bibliography/shimoura_2018.html new file mode 100644 index 0000000..39a6a57 --- /dev/null +++ b/bibliography/shimoura_2018.html @@ -0,0 +1,191 @@ + + + + + + + + + + + + [Re] The cell-type specific cortical microcircuit: relating + structure and activity in a full-scale spiking network + model + + + + + + + + + + + +
+ +
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+ ReScience C +
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Shimoura, R.O., Kamij, N.L., Pena, R.F.O., et al. 2018. [Re] The cell-type specific cortical microcircuit: relating + structure and activity in a full-scale spiking network + model. ReScience 4, 1, #2.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Article (PDF):https://github.com/ReScience-Archives/ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-2017/blob/master/article/ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-2017.pdf
Title:[Re] The cell-type specific cortical microcircuit: relating + structure and activity in a full-scale spiking network + model
Author(s):Shimoura, Renan O. and Kamij, Nilton L. and Pena, Rodrigo F.O. and Cordeiro, Vinicius L. and Ceballos, Cesar C. and Romaro, Cecilia and Roque, Antonio C.
Journal:ReScience
Year:2018
Month:may
Volume:4
Issue:1
Number:#2
DOI:10.5281/zenodo.1244116
Code URL:https://github.com/ReScience-Archives/ShimouraR-KamijiNL-PenaRFO-CordeiroVL-CeballosCC-RomaroC-RoqueAC-2017/
Code DOI:10.5281/zenodo.1244116
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/43
Cite as:Shimoura, R.O., Kamij, N.L., Pena, R.F.O., et al. 2018. [Re] The cell-type specific cortical microcircuit: relating + structure and activity in a full-scale spiking network + model. ReScience 4, 1, #2.
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+ + + + + + + diff --git a/bibliography/stojic_2017.html b/bibliography/stojic_2017.html new file mode 100644 index 0000000..0a99d83 --- /dev/null +++ b/bibliography/stojic_2017.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] How learning can guide evolution + + + + + + + + + + + +
+ +
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Stojić, H. 2017. [Re] How learning can guide evolution. ReScience 3, 1, #8.

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Article (PDF):https://github.com/ReScience-Archives/Stojic-2017/blob/master/article/Stojic-2017.pdf
Title:[Re] How learning can guide evolution
Author(s):Stojić, Hrvoje
Journal:ReScience
Year:2017
Month:sep
Volume:3
Issue:1
Number:#8
DOI:10.5281/zenodo.890884
Code URL:https://github.com/ReScience-Archives/Stojic-2017
Code DOI:10.5281/zenodo.890884
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/36
Cite as:Stojić, H. 2017. [Re] How learning can guide evolution. ReScience 3, 1, #8.
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+ + + + + + + diff --git a/bibliography/stollmeier_2017.html b/bibliography/stollmeier_2017.html new file mode 100644 index 0000000..b6b6664 --- /dev/null +++ b/bibliography/stollmeier_2017.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] A simple rule for the evolution of cooperation on graphs and social networks + + + + + + + + + + + +
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Stollmeier, F. 2017. [Re] A simple rule for the evolution of cooperation on graphs and social networks. ReScience 3, 1, #5.

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Article (PDF):https://github.com/ReScience-Archives/Stollmeier-2017/blob/master/article/Stollmeier-2017.pdf
Title:[Re] A simple rule for the evolution of cooperation on graphs and social networks
Author(s):Stollmeier, Frank
Journal:ReScience
Year:2017
Month:aug
Volume:3
Issue:1
Number:#5
DOI:10.5281/zenodo.847732
Code URL:https://github.com/ReScience-Archives/Stollmeier-2017
Code DOI:10.5281/zenodo.847732
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/27
Cite as:Stollmeier, F. 2017. [Re] A simple rule for the evolution of cooperation on graphs and social networks. ReScience 3, 1, #5.
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+ + + + + + + diff --git a/bibliography/tennoe_2019.html b/bibliography/tennoe_2019.html new file mode 100644 index 0000000..744f715 --- /dev/null +++ b/bibliography/tennoe_2019.html @@ -0,0 +1,191 @@ + + + + + + + + + + + + [Re] Fast-Activating Voltage- and Calcium-Dependent + Potassium (BK) Conductance Promotes Bursting in Pituitary + Cells: A Dynamic Clamp Study + + + + + + + + + + + +
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Tennøe, S., Hodne, K., Haug, T.M., Weltzien, F.-A., Einevoll, G.T., and Halnes, G. 2019. [Re] Fast-Activating Voltage- and Calcium-Dependent + Potassium (BK) Conductance Promotes Bursting in Pituitary + Cells: A Dynamic Clamp Study. ReScience 5, 1, #2.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Article (PDF):https://github.com/ReScience-Archives/Tenn-e-Hodne-Haug-Weltzien-Einevoll-Halnes-2019/blob/master/article/tenn%C3%B8e-hodne-haug-weltzien-einevoll-halnes-2018.pdf
Title:[Re] Fast-Activating Voltage- and Calcium-Dependent + Potassium (BK) Conductance Promotes Bursting in Pituitary + Cells: A Dynamic Clamp Study
Author(s):Tennøe, Simen and Hodne, Kjetil and Haug, Trude M. and Weltzien, Finn-Arne and Einevoll, Gaute T. and Halnes, Geir
Journal:ReScience
Year:2019
Month:may
Volume:5
Issue:1
Number:#2
DOI:10.5281/zenodo.2611252
Code URL:https://github.com/ReScience-Archives/Tenn-e-Hodne-Haug-Weltzien-Einevoll-Halnes-2019
Code DOI:-
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/53
Cite as:Tennøe, S., Hodne, K., Haug, T.M., Weltzien, F.-A., Einevoll, G.T., and Halnes, G. 2019. [Re] Fast-Activating Voltage- and Calcium-Dependent + Potassium (BK) Conductance Promotes Bursting in Pituitary + Cells: A Dynamic Clamp Study. ReScience 5, 1, #2.
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+ + + + + + + diff --git a/bibliography/topalidou_2015.html b/bibliography/topalidou_2015.html new file mode 100644 index 0000000..0ff51fb --- /dev/null +++ b/bibliography/topalidou_2015.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] Interaction between cognitive and motor cortico-basal + ganglia loops during decision making: a computational study + + + + + + + + + + + +
+ +
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+ ReScience C +
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Topalidou, M. and Rougier, N.P. 2015. [Re] Interaction between cognitive and motor cortico-basal + ganglia loops during decision making: a computational study. ReScience 1, 1, #1.

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Article (PDF):https://github.com/ReScience-Archives/ReScience-Entry-Topalidou-Rougier-2015/raw/1.0/article/article.pdf
Title:[Re] Interaction between cognitive and motor cortico-basal + ganglia loops during decision making: a computational study
Author(s):Topalidou, Meropi and Rougier, Nicolas P.
Journal:ReScience
Year:2015
Month:aug
Volume:1
Issue:1
Number:#1
DOI:10.5281/zenodo.27944
Code URL:https://github.com/ReScience-Archives/ReScience-Entry-Topalidou-Rougier-2015
Code DOI:10.5281/zenodo.27944
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/3
Cite as:Topalidou, M. and Rougier, N.P. 2015. [Re] Interaction between cognitive and motor cortico-basal + ganglia loops during decision making: a computational study. ReScience 1, 1, #1.
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+ + + + + + + diff --git a/bibliography/viejo_2016.html b/bibliography/viejo_2016.html new file mode 100644 index 0000000..2cd332f --- /dev/null +++ b/bibliography/viejo_2016.html @@ -0,0 +1,187 @@ + + + + + + + + + + + + [Re] Speed/accuracy trade-off between the habitual and the + goal-directed process + + + + + + + + + + + +
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Viejo, G., Girard, B., and Khamassi, M. 2016. [Re] Speed/accuracy trade-off between the habitual and the + goal-directed process. ReScience 2, 1, #1.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Article (PDF):https://github.com/ReScience-Archives/Viejo-Girard-Khamassi-2016/raw/master/article/viejo_girard_khamassi.pdf
Title:[Re] Speed/accuracy trade-off between the habitual and the + goal-directed process
Author(s):Viejo, Guillaume and Girard, Benoît and Khamassi, Mehdi
Journal:ReScience
Year:2016
Month:feb
Volume:2
Issue:1
Number:#1
DOI:10.5281/zenodo.45852
Code URL:https://github.com/ReScience-Archives/Viejo-Girard-Khamassi-2016
Code DOI:10.5281/zenodo.45852
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/14
Cite as:Viejo, G., Girard, B., and Khamassi, M. 2016. [Re] Speed/accuracy trade-off between the habitual and the + goal-directed process. ReScience 2, 1, #1.
+ + + + + +
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+ + + + + + + diff --git a/bibliography/vitay_2016.html b/bibliography/vitay_2016.html new file mode 100644 index 0000000..271ed92 --- /dev/null +++ b/bibliography/vitay_2016.html @@ -0,0 +1,183 @@ + + + + + + + + + + + + [Re] Robust timing and motor patterns by taming chaos in recurrent neural networks + + + + + + + + + + + +
+ +
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Vitay, J. 2016. [Re] Robust timing and motor patterns by taming chaos in recurrent neural networks. ReScience 2, 1, #5.

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Article (PDF):https://github.com/ReScience-Archives/Vitay-2016/raw/master/article/vitay-2016.pdf
Title:[Re] Robust timing and motor patterns by taming chaos in recurrent neural networks
Author(s):Vitay, Julien
Journal:ReScience
Year:2016
Month:oct
Volume:2
Issue:1
Number:#5
DOI:10.5281/zenodo.159545
Code URL:https://github.com/ReScience-Archives/Vitay-2016
Code DOI:10.5281/zenodo.159545
Data URL:-
Data DOI:-
Review URL:https://github.com/ReScience/ReScience-submission/pull/19
Cite as:Vitay, J. 2016. [Re] Robust timing and motor patterns by taming chaos in recurrent neural networks. ReScience 2, 1, #5.
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+ top: 9px; + right: 30px; + background-color: #fdfdfd; + border: 1px solid #e8e8e8; + border-radius: 5px; + text-align: right; } + .site-nav .menu-icon { + display: block; + float: right; + width: 36px; + height: 26px; + line-height: 0; + padding-top: 10px; + text-align: center; } + .site-nav .menu-icon > svg { + width: 18px; + height: 15px; } + .site-nav .menu-icon > svg path { + fill: #424242; } + .site-nav .trigger { + clear: both; + display: none; } + .site-nav:hover .trigger { + display: block; + padding-bottom: 5px; } + .site-nav .page-link { + display: block; + padding: 5px 10px; } } + +/** + * Site footer + */ +.site-footer { + border-top: 1px solid #e8e8e8; + padding: 30px 0; } + +.footer-heading { + font-size: 18px; + margin-bottom: 15px; } + +.contact-list, +.social-media-list { + list-style: none; + margin-left: 0; } + +.footer-col-wrapper { + font-size: 15px; + color: #828282; + margin-left: -15px; } + +.footer-col { + float: left; + margin-bottom: 15px; + padding-left: 15px; 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} + +.site-nav a:hover { + text-decoration: none; + color: #ce232b; } + +.post-content h2 { + font-size: 20px; } + @media screen and (max-width: 800px) { + .post-content h2 { + font-size: 16px; } } +.post-content h3 { + font-size: 16px; } + @media screen and (max-width: 800px) { + .post-content h3 { + font-size: 16px; } } +.post-content h4 { + font-size: 16px; } + @media screen and (max-width: 800px) { + .post-content h4 { + font-size: 16px; } } + +a.bibtag { + padding: .25em .5em .1em .5em; + background-color: #ce232b; + color: white; + border-radius: 2px; } + +.collapse { + font-size: 90%; + color: black; + background-color: #fff0f0; + border: 1px solid black; } + +pre, code { + border: none; + color: #555555; + background: none; } + +.post-tag, .post-tag a { + color: #fff; + background-color: #aaa; + text-align: center; + white-space: nowrap; + vertical-align: middle; + padding: 2px 12px; + line-height: 1.5; + border-radius: 3px; } + +.footer-col-wrapper { + font-size: 12px; + text-align: center; + border-top: 1px solid #e8e8e8; + padding: 10px 0; } + +.site-footer { + border: none; + padding: 0; } + +.highlight { + background: #f0f0ff; } + +li p small { + display: block; + width: 50%; + line-height: 1.25em !important; + /*padding-left: 10px;*/ + border-top: 1px solid black; + margin-top: 0.50em; + padding-top: 0.50em; + margin-bottom: 2.00em; } + +ol.bibliography { + font-size: 100%; + line-height: 1.25em; } + +table { + clear: both; } + +table td { + vertical-align: top; } + +table td:first-child { + width: 20%; } + +.thumbnail { + border: 1px solid black; } + +div.bib-entry-highlight { + width: 100%; + padding: 1.5em; + color: white; + background-color: #ce232b; } + +img.ten-years-challenge { + /* float: right; + width: 25%; */ + border: 1px solid black; } diff --git a/css/main.scss b/css/main.scss deleted file mode 100755 index 12238f8..0000000 --- a/css/main.scss +++ /dev/null @@ -1,162 +0,0 @@ ---- -# Only the main Sass file needs front matter (the dashes are enough) ---- -@charset "utf-8"; - - - -// Our variables -$base-font-family: Helvetica, Arial, sans-serif; -$base-font-size: 16px; -$small-font-size: $base-font-size * 0.875; -$base-line-height: 1.35; - -$spacing-unit: 30px; - -$text-color: #111; -$background-color: #fdfdfd; -$brand-color: #2a7ae2; - -$grey-color: #828282; -$grey-color-light: lighten($grey-color, 40%); -$grey-color-dark: darken($grey-color, 25%); - -// Width of the content area -$content-width: 800px; - -$on-palm: 600px; -$on-laptop: 800px; - - - -// Using media queries with like this: -// @include media-query($on-palm) { -// .wrapper { -// padding-right: $spacing-unit / 2; -// padding-left: $spacing-unit / 2; -// } -// } -@mixin media-query($device) { - @media screen and (max-width: $device) { - @content; - } -} - - - -// Import partials from `sass_dir` (defaults to `_sass`) -@import - "base", - "layout", - "syntax-highlighting" -; - - -/*****************************/ -/* ReScience custom settings */ -/*****************************/ - -h1, h2, h3, h4, h5, h6 { - color: #ce232b; - padding-top: 1em; - font-weight: 500; -} - -.site-header strong { - color: #ce232b; - font-weight: 600; -} - -.site-header { - border: none; - min-height: 150px; -} - -.site-title { - line-height: 125px; -/* margin-left: -50px;*/ -} - -a.site-title:hover { - text-decoration: none; - color: #ce232b; -} - -.site-nav a { - font-size: 14px; - color: #ce232b; - font-weight: 400; -} - -.site-nav a:hover { - text-decoration: none; - color: #ce232b; -} - -.post-content { - h2 { - font-size: 20px; - @include media-query($on-laptop) { - font-size: 16px; - } - } - h3 { - font-size: 16px; - - @include media-query($on-laptop) { - font-size: 16px; - } - } - h4 { - font-size: 16px; - @include media-query($on-laptop) { - font-size: 16px; - } - } -} - -pre,code { - border: none; - color: #555555; - background: none; -} - -.post-tag, .post-tag a { - color: #fff; - background-color: #aaa; - text-align: center; - white-space: nowrap; - vertical-align: middle; - padding: 2px 12px; - line-height: 1.5; - border-radius: 3px; -} - -.footer-col-wrapper { - font-size: 12px; - text-align: center; - border-top: 1px solid $grey-color-light; - padding: 10px 0; -} - - -.site-footer { -// border-top: 1px solid $grey-color-light; - border: none; - padding: 0; -} - -.highlight { - background: #f0f0ff; -} - -li p small { - display: block; - width: 50%; - line-height: 1.25em !important; - /*padding-left: 10px;*/ - border-top: 1px solid black; - margin-top: 0.50em; - padding-top: 0.50em; - margin-bottom: 2.00em; -} diff --git a/edit/index.html b/edit/index.html new file mode 100644 index 0000000..610f99f --- /dev/null +++ b/edit/index.html @@ -0,0 +1,251 @@ + + + + + + + + + + + + ReScience C + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ + + +
+

The reviewing process

+ +

A submission takes the form of an issue. If you’re unfamiliar with GitHub, do +not hesitate to ask advices and informations to the editor in charge of editing +the submission. Reviewers unfamiliar with git should have a look at +http://git-lectures.github.io.

+ +

To review a submission, you’ll first have to clone the author’s repository onto +your desktop environment and each time an author update the manuscript or code +to get reviewer’s comment into account, you’ll have to update your local copy +using the git pull command.

+ +

Reviewer guidelines

+ +

Successful replications

+ +

Most articles in ReScience C report a successful replication of the +results (figures, tables, …) of previously published research work. +A full replication covers all the results of the original work, whereas +a partial replication covers only a subset of the results.

+ +

The main criteria for acceptance of a successful replication are

+ +
    +
  1. +

    The actual replication of the research. The reviewer must evaluate +the authors’ claims about a successful replication, applying the +standards of the field.

    +
    2. +
  2. +

    Reproducibility of the replication. The reviewers must be able +to run the proposed implementation on their computer, and obtain +the same results as the authors with the limits of the state +of the art of the field.

    +
    3. +
  3. +

    Clarity of the code and the instructions for running it. +Uncommented or obfuscated code is as bad as no code at all.

    +
    4. +
  4. +

    Clarity and completeness of the accompanying article, in which the +authors should clearly state why they think they have replicated +the paper (same figures, same graphics, same behavior, etc.) and +explain any obstacles they have encountered during the replication +work. The reviewers should also consider if the article is sufficiently +self-contained.

    +
    5. +
+ +

The primary goal of the review is not to decide whether to accept or +reject a submission, but to help the authors improve their work until +it meets the ReScience C quality standards. Since ReScience C +targets replication of already published research, there is no need to +judge the relevance or novelty of the work. Every replication that +meets the criteria listed above is welcome in ReScience C. +Rejection remains of course a possibility, in the case that the +authors are not able or willing to improve their submission as +deemed necessary by the reviewers.

+ +

When evaluating the criteria for acceptance, reviewers need to apply +the standards of their field of research. There are no absolute +criteria for two results/figures being equal, so both the success and +the reproducibility of the replication must be judged according to +the degree of equality that can be achieved given the state of the +art of the field. The clarity of the code and instructions must also +be judged in the light of the conventions of the field. As a general +goal, any competent researcher in the field should understand the +paper and be able to understand and run the code. The use of +software packages that are mainstream in the field is encouraged, +but not strictly required. The less well-known a software package +is, the more explanation authors should provide concerning its +capabilities and use.

+ +

Failed replications

+ +

A replication attempt can lead to the finding that the results of the original +paper cannot be reproduced, suggesting a critical mistake or omission in the +original work that cannot be fixed. The failure can concern some or all of the +results. ReScience C accepts reports on replication failures, but requires a +particularly careful examination by the reviewers. The authors must describe in +detail why they believe that the original work is mistaken, and the reviewers +must be convinced by the reasoning offered by the authors.

+ +

Authors who are confronted with replication failure are strongly encouraged +to contact the authors of the original work and try to explore the causes +of the replication failure in collaboration with them. This is, however, not +a requirement for publication in ReScience C.

+ +

The editing process

+ +

The role of a scientific editor is to manage a submission from start to end, +i.e. from the initial acknowledgment request by the editor-in-chief to the +final publication. As an editor, your goal is to help authors improve their +submission in order to meet the journal’s quality standards and to ensure that +anyone can re-use the published code. Depending on the specific domain, an +editor might request the article to follow best practices of the domain.

+ +

Editor guidelines

+ +
    +
  • When a new submission is +made (i.e. a new issue has been opened), you can assign yourself in order to +be the editor or you can accept an invitation to edit the submission.
    • +
  • Once you’ve accepted, you can either reject the submission and close the +issue (you’ll have to motivate such decision) or accept the +submission. You’ll then need to find and invite at least two reviewers (from +within the same issue)
    • +
  • Once you’ve found the two reviewers, you can start the review.
    • +
  • During the review, reviewers are free to interact with the authors to ask for +clarification or change in any file that is part of the submission.
    • +
  • The main criterion for acceptance is either: +
      +
    • Replication of the original research with a clear statement by the authors +explaining why they think they have replicated the paper (same figures, +same graphics, same behavior, etc.).
      • +
    • Non-replication of the original research with a clear statement by the +authors explaining why they believe that it cannot be replicated .
      • +
    • Source code without any accompanying article is also a criterion for +rejection since we’re not human compilers (well not all of us at least).
      • +
    +
    • +
  • Don’t forget to check that there is a license in the code repository. Authors +can choose whatever open license they prefer (see the Debian Free Software +Guidelines) but they need +to choose one.
    • +
  • If both reviewers agree, the paper can be accepted.
    • +
+ +

The publication process

+ +

The publication is now almost automatic but still requires some manual steps +that are given in the README of the +articles repository.

+ +

After publication, you can try to contact the editor and the authors of the +original article to tell them about the successful (or unsuccessful) replication +of their work.

+ +

You can also tweet about the new paper, with CC to @ReScienceEds.

+ +

Finally, you can close the issue.

+ + +
+ +
+ +
+
+ + + + + + + diff --git a/faq/index.html b/faq/index.html new file mode 100644 index 0000000..4fe3849 --- /dev/null +++ b/faq/index.html @@ -0,0 +1,288 @@ + + + + + + + + + + + + ReScience C + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ + + +
+

Frequently Asked Questions

+ +

If your question is not answered below, please create an +issue on GitHub and ask it there.

+ +

Can I help?

+ +

Yes! You can:

+ +
    +
  • Become a reviewer by commenting on this issue (see + our current list of reviewers + for the information we would like to have about you)
    • +
  • Submit paper for the work you’ve already replicated
    • +
  • Spread the word about ReScience C in your community +(twitter, mailing lists, blogs, etc.)
    • +
+ +

What’s the difference between replication and reproduction?

+ +

There is no consensus yet on what exactly these two terms mean, so +here is how we understand and use them.

+ +

Reproduction of a computational study means running the same +computation on the same input data, and then checking if the results +are the same, or at least “close enough” when it comes to numerical +approximations. Reproduction can be considered as software testing at +the level of a complete study.

+ +

Replication of a scientific study (computational or other) means +repeating a published protocol, respecting its spirit and intentions +but varying the technical details. For computational work, this would +mean using different software, running a simulation from different +initial conditions, etc. The idea is to change something that everyone +believes shouldn’t matter, and see if the scientific conclusions are +affected or not.

+ +

Reproduction verifies that a computation was recorded with enough +detail that it can be analyzed later or by someone else. Replication +explores which details matter for reaching a specific scientific +conclusion. A replication attempt is most useful if reproducibility +has already been verified. Otherwise, if replication fails, leads to +different conclusions, you cannot trace back the differences in the +results to the underlying code and data.

+ +

In the ideal world, the reproducibility of computational studies would +be checked automatically before publication. In the real world, most +published studies do not even claim to be reproducible, because the code +or the input data are not made public. Given this situation, +a ReScience C publication provides two important services: by replicating +the original work, it provides an independent implementation of the +original computational protocol, and by making this new implementation +public, it is reproducible and thus a safer basis for future research +to build on.

+ +

What do the title prefixes Re, Rp, ¬Re, and ¬Rp mean?

+

Re means replication. Rp means reproduction. +Either one can be negated in case of failure to give: ¬Re and ¬Rp.

+ +

Are there any publication fees?

+ +

No. ReScience C promotes open access and relies on the volunteer work of +editors and reviewers. And the free hosting by GitHub.

+ +

ReScience C is a platinum open-access journal, which means that authors do +not pay to publish and readers do not pay to read.

+ +

Can I submit a paper using proprietary tools such as MATLAB?

+ +

No. If we aim at replicability, we have to make sure the proposed +implementation allows anyone to re-run and understand the code without any +barriers. Proprietary software constitutes such a barrier because of their +price and their closed nature. An implementation specifically targeting a free +alternative such as Octave will be +accepted though.

+ +

Is it mandatory to have an open-source license on the code?

+ +

Yes. The code accompanying ReScience C articles will be archived at +Zenodo along with the article and data, entirely under +open licenses. This is part of the open access principle underlying ReScience +C. For the choice of a license for the code, we refer to the the Debian Free +Software Guidelines.

+ +

Can I submit the replication of my own research?

+ +

No. Mistakes in the implementation of research questions and methods are often +due to biases authors invariably have, consciously or not. One’s biases will +inevitably carry over to how one approaches a replication. Perhaps even more +importantly, we aim at the cross-fertilization of research and trying to +replicate the work of one’s peers might pave the way for a future +collaboration, or may give rise to new ideas as a result of the replication +effort.

+ +

Can I suggest a replication?

+ +

Yes. If you want to suggest an article for a replication, just open a new +issue in the call for +replication repository and give the +reference of the original article and possibly the reason you would like to see +this article replicated (please refrain from suggesting your own work). Note +that you’re also encouraged to register as a reviewer such that you can review +the replication you’ve been proposing if someone actually takes up the +challenge.

+ +

If you’re looking for some challenge, you can also look at the current list of +suggestions.

+ +

If my submission is rejected, can I resubmit it?

+ +

This depends on the reason your submission was rejected. If the original +research has already been replicated previously (in ReScience C or elsewhere), +it is unlikely we’ll consider another replication, even if you think your +implementation is better. However, if your submission has been rejected because +reviewers cannot make it run, you are encouraged to re-submit once the +identified problems have been solved.

+ +

What if I fail to replicate a research result?

+ +

Some research may not be replicable. Before declaring a research result +non-replicable, we require extra caution to be taken. In addition to scrutiny +of your submission by reviewers and editors, we will contact the authors of the +original research, and issue a challenge to the ReScience C community to spot +and report (using the issue tracker) errors in your implementation. If no +errors are found, your work will be accepted and the original research will be +declared non-replicable.

+ +

Is there a preferred implementation language?

+ +

We favor a Python implementation because this language offers a scientific +programming stack that can handle research in many +domains of science (see for example the Scipy +2015 and EuroScipy +2015 conferences). Python is also often +reported by scientists to easier to learn and use than other languages. +Furthermore, using Python might allow us to use the +IPython notebook and the upcoming +Jupyter environments.

+ +

However, other languages or tools are acceptable if they are mainstream in the +respective domain of research.

+ +

I’m a student, can I submit?

+ +

Yes! Students are strongly encouraged to submit their work. Although the +ReScience C publishing model is a bit different from other academic journals, +it can give students a first experience at peer-reviewed scholarly publishing, +including meeting standards of scientific rigor and addressing reviewers’ +comments. Publishing in ReScience C is also a way to actively contribute to +open science while adding to one’s publication record.

+ +

How do I know if my replication is successful?

+ +

This depends mainly on the original paper introducing the research results to +be replicated. Results might be presented in a qualitative or quantitative way +and you’ll have to clearly state why you think your implementation of a method +or protocol is a faithful replication of the original results.

+ +

What kind of research can I replicate?

+ +

Any computational research in any domain of science provided an +editor from the Board has the expertise to edit your +submission. Our editorial board is growing to increase the scientific domains +being covered. If no editor is able to edit your submission, you may +propose a guest editor (who must be willing to work with our GitHub-based +editorial processes).

+ +

Does ReScience C issue DOIs (Digital Object Identifiers)?

+ +

ReScience C itself does not, but every article published in ReScience C +receives a DOI from, and is indexed by +Zenodo.

+ +

What is the preferred format for the accompanying article?

+ +

We prefer LaTeX using the provided +template but Word or OpenOffice are +also fine if the result is comparable to the PDF produced by our template.

+ + +
+ +
+ +
+
+ + + + + + + diff --git a/feed.xml b/feed.xml index a3819fc..dfd2452 100644 --- a/feed.xml +++ b/feed.xml @@ -1,31 +1,220 @@ ---- -layout: null -permalink: /feed.xml ---- - {{ site.title | xml_escape }} - {{ site.description | xml_escape }} - {{ site.url }}{{ site.baseurl }}/ - - {{ site.time | date_to_rfc822 }} - {{ site.time | date_to_rfc822 }} - Jekyll v{{ jekyll.version }} - {% for post in site.posts limit:10 %} - - {{ post.title | xml_escape }} - {{ post.content | xml_escape }} - {{ post.date | date_to_rfc822 }} - {{ post.url | prepend: site.baseurl | prepend: site.url }} - {{ post.url | prepend: site.baseurl | prepend: site.url }} - {% for tag in post.tags %} - {{ tag | xml_escape }} - {% endfor %} - {% for cat in post.categories %} - {{ cat | xml_escape }} - {% endfor %} - - {% endfor %} + ReScience C + Reproducible Science is good.<br/> Replicated Science is better. + http://rescience.github.io/ + + Wed, 28 Jan 2026 12:13:38 +0100 + Wed, 28 Jan 2026 12:13:38 +0100 + Jekyll v3.9.3 + + + Ten Years Reproducibility Challenge + <p>Did you ever try to run an old code that you wrote for a scientific article you +published years ago? Did you encounter any problems? Were you successful? We +are curious to hear your story. This is the reason why we are editing a special +issue of ReScience to collect these stories.</p> + +<p>The ten years reproducibility challenge is an invitation for researchers to try +to run the code they’ve created for a scientific publication that was published +more than <strong>ten years ago</strong>. This code can be anything (statistical analysis, +numerical simulation, data processing, etc.), can be written in any language +and can address any scientific domain. The only mandatory condition to enter +the challenge is to have published a scientific article <strong>before 2010</strong>, in a +journal or a conference with proceedings, which contains results produced by +code, irrespectively of whether this code was published in some form at the +time or not.</p> + +<p>Note that we do not ask you to write a new version of your old code. We ask you +instead to <strong>try to make your old code to run on modern hardware/software</strong> +(with minimal modifications) in order to check if you can obtain the exact same +results that were published at least ten years ago.</p> + +<p>Sounds easy? We have good reasons to think this might be more difficult than you +think. And maybe the first problem you’ll have to solve is to find your own source +code.</p> + +<p>More information at: <a href="http://rescience.github.io/ten-years/">rescience.github.io/ten-years</a></p> + + + Fri, 11 Oct 2019 00:00:00 +0200 + http://rescience.github.io/news/2019/10/11/TenYears.html + http://rescience.github.io/news/2019/10/11/TenYears.html + + + news + + + + + ReScience (R)evolution + <p>Four years ago, we launched ReScience, a new scientific journal aimed at +publishing the replication of existing computational research. Since ReScience +published its first article, things have been going steadily. We are still +alive, independent and without a budget. In the meantime, we have published +around 25 articles and the initial has grown from around 10 to roughly 100 +members (editors and reviewers), we have advertised ReScience at several +conferences worldwide, gave some interviews, and published an article +introducing ReScience in PeerJ Computer Science. Based on our experience at +managing the journal during these four years, we thought that time was ripe for +some changes. Read our +<a href="https://zenodo.org/record/3069619/files/article.pdf">editorial</a> if you want to +know more.</p> + + Thu, 23 May 2019 00:00:00 +0200 + http://rescience.github.io/news/2019/05/23/Redesign.html + http://rescience.github.io/news/2019/05/23/Redesign.html + + + news + + + + + Sustainable computational science: the ReScience initiative + <p>We just published our white paper on ReScience in +<a href="https://peerj.com/articles/cs-142/">PeerJ</a></p> + +<p><strong>Abstract</strong>: Computer science offers a large set of tools for +prototyping, writing, running, testing, validating, sharing and reproducing +results; however, computational science lags behind. In the best case, authors +may provide their source code as a compressed archive and they may feel +confident their research is reproducible. But this is not exactly true. James +Buckheit and David Donoho proposed more than two decades ago that an article +about computational results is advertising, not scholarship. The actual +scholarship is the full software environment, code, and data that produced the +result. This implies new workflows, in particular in peer-reviews. Existing +journals have been slow to adapt: source codes are rarely requested and are +hardly ever actually executed to check that they produce the results advertised +in the article. ReScience is a peer-reviewed journal that targets computational +research and encourages the explicit replication of already published research, +promoting new and open-source implementations in order to ensure that the +original research can be replicated from its description. To achieve this goal, +the whole publishing chain is radically different from other traditional +scientific journals. ReScience resides on GitHub where each new implementation +of a computational study is made available together with comments, +explanations, and software tests.</p> + +<p><strong>References</strong>: N.P. Rougier et al., (2017) <strong>Sustainable computational science: the +ReScience initiative</strong>. PeerJ Computer Science 3:e142. <a href="https://doi.org/10.7717/peerj-cs.142">DOI +doi.org/10.7717/peerj-cs.142</a></p> + + Mon, 18 Dec 2017 00:00:00 +0100 + http://rescience.github.io/news/2017/12/18/ReScience-arXiv.html + http://rescience.github.io/news/2017/12/18/ReScience-arXiv.html + + + news + + + + + Call for replication + <p>It is now possible to suggest an article for a replication. Just +<a href="https://github.com/ReScience/call-for-replication/issues/new">open a new issue</a> +in the +<a href="https://github.com/ReScience/call-for-replication">call for replication repository</a> +and give the reference of the original article and possibly the reason you +would like to see this article replicated (please refrain from suggesting your +own work). Note that you’re also encouraged to register as a reviewer such that +you can review the replication you’ve been proposing if someone actually takes +up the challenge.</p> + +<p>If you’re looking for some challenge, you can also look at the +<a href="https://github.com/ReScience/call-for-replication/issues">current list of suggestions</a>.</p> + + Wed, 19 Oct 2016 00:00:00 +0200 + http://rescience.github.io/news/2016/10/19/Call-For-Replication.html + http://rescience.github.io/news/2016/10/19/Call-For-Replication.html + + + news + + + + + You can help by becoming a reviewer + <p>ReScience is slowly gaining momentum and we currently have 4 submissions to +review. If you’re interested in helping ReScience and reproducibility, you can +become a reviewer. What you need is a github account, a one line description of +your expertise (see the <a href="http://rescience.github.io/board/">Board</a> for some +examples) and to <a href="https://github.com/ReScience/ReScience/issues/27">tell us</a> you’re interested such that we can add you to the board. You can also <a href="https://github.com/ReScience/ReScience-submission/subscription">follow</a> the <a href="https://github.com/ReScience/ReScience-submission">submission</a> repository and propose your help whenever a submission falls into your expertise domain.</p> + + + Sat, 02 Jul 2016 00:00:00 +0200 + http://rescience.github.io/news/2016/07/02/Reviewers.html + http://rescience.github.io/news/2016/07/02/Reviewers.html + + + news + + + + + New year, new challenges ahead + <p>Even though open and reproducible science is gaining fast ground, there still +exists a large number of published computational researches that are just +awaiting replication. Why not pick your favorite paper and try to replicate it +? If you’re interested in this specific paper, chances are that your replication +will also be interesting for a lot of researchers.</p> + + Thu, 07 Jan 2016 00:00:00 +0100 + http://rescience.github.io/news/2016/01/07/NewYear.html + http://rescience.github.io/news/2016/01/07/NewYear.html + + + news + + + + + ReScience: A Scientific Journal Living on Github + <p><a href="http://www.labcritics.com">LabCritics</a> kindly made a <a href="http://www.labcritics.com/rescience-a-scientific-journal-with-github-at-its-core-4729/?utm_source=@labcritics">post</a> introducing Re<strong>Science</strong> and explaining its goals: “Computational research is set to get new open source journal solely for publishing implementations of algorithms and codes already published. Termed ReScience (Replicated Science – I guess [<strong>note</strong>: yes]), the journal uses and exists solely on Github, a popular Web-based Git repository service, offering all of the distributed revision control and source code management functionality of Git.”</p> + + + Sun, 06 Sep 2015 00:00:00 +0200 + http://rescience.github.io/news/2015/09/06/LabCritics.html + http://rescience.github.io/news/2015/09/06/LabCritics.html + + + news + + + + + Official creation + <p>It’s our great pleasure to announce the creation of Re<strong>Science</strong> which is a +peer-reviewed journal that targets computational research and encourages the +explicit replication of already published research, promoting new and +open-source implementations in order to ensure that the original research is +reproducible.</p> + + Tue, 01 Sep 2015 00:00:00 +0200 + http://rescience.github.io/news/2015/09/01/journal-start.html + http://rescience.github.io/news/2015/09/01/journal-start.html + + + news + + + + + Review process test is over + <p>We’ve been testing the +<a href="https://github.com/ReScience/ReScience-submission/pull/3">review process</a> with +Tiziano Zito (editor), Benoît Girard (reviewer) and Mehdi Khamassi +(reviewer). They helped smoothing the whole process and we’re ready for mass +production! But let’s wait for a second review…</p> + + Mon, 10 Aug 2015 00:00:00 +0200 + http://rescience.github.io/news/2015/08/10/ReviewTest.html + http://rescience.github.io/news/2015/08/10/ReviewTest.html + + + news + + + diff --git a/images/ten-years-challenge.pdf b/images/ten-years-challenge.pdf new file mode 100644 index 0000000..a6b24fd Binary files /dev/null and b/images/ten-years-challenge.pdf differ diff --git a/images/ten-years-challenge.png b/images/ten-years-challenge.png new file mode 100644 index 0000000..6bddb4e Binary files /dev/null and b/images/ten-years-challenge.png differ diff --git a/index.html b/index.html new file mode 100644 index 0000000..5b86608 --- /dev/null +++ b/index.html @@ -0,0 +1,418 @@ + + + + + + + + + + + + ReScience C + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ + + +
+

Reproducible Science is good. Replicated Science is better.

+ +

ReScience C is a platinum open-access peer-reviewed journal that targets +computational research and encourages the explicit replication of +already published research, promoting new and open-source implementations in +order to ensure that the original research is reproducible. +You can read about the ideas behind ReScience C in the article +Sustainable computational science: the ReScience initiative

+ +

To achieve this goal, the whole publishing chain is radically different from +other traditional scientific journals. ReScience C lives on +GitHub where each new implementation of a +computational study is made available together with comments, explanations and +tests. Each submission takes the form of an issue that is publicly reviewed and +tested in order to guarantee that any researcher can re-use it. If you ever +replicated computational results (or failed at) from the literature in your +research, ReScience C is the perfect place to publish your new implementation.

+ +

ReScience C is collaborative and open by design. Everything can be forked and +modified. Don’t hesitate to write a submission, join us and +to become a reviewer.

+ +


+ +

Latest publications

+ +
  1. + + + + + Replication + + in Machine Learning + + (Python) + + + + + + + + | 10.5281/zenodo.18401497 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hudovernik, V., Rot, Ž., Vovk, K., Škodnik, L., and Zajc, L.Č. 2026. Learning with Noisy Labels [ Re]visited. ReScience C 11, 1, #2. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computer Graphics + + (Python) + + + + + + + + | 10.5281/zenodo.18400484 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Perazzo, D., Castro, D.G.N.S., Velho, L., and Figueiredo, L.H. de. 2026. [Re] Curve-Fitting with Piecewise Parametric Cubics. ReScience C 11, 1, #1. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.16529268 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Reynes, M. and Aussel, A. 2025. [Re] Model of thalamocortical slow-wave sleep oscillations and transitions to activated states. ReScience C 10, 1, #5. +
    +
    + + + +
+


+ +

Latest News

+
    + + +
  • +

    Ten Years Reproducibility Challenge + Oct 11, 2019

    +

    Did you ever try to run an old code that you wrote for a scientific article you +published years ago? Did you encounter any problems? Were you successful? We +are curious to hear your story. This is the reason why we are editing a special +issue of ReScience to collect these stories.

    + +

    The ten years reproducibility challenge is an invitation for researchers to try +to run the code they’ve created for a scientific publication that was published +more than ten years ago. This code can be anything (statistical analysis, +numerical simulation, data processing, etc.), can be written in any language +and can address any scientific domain. The only mandatory condition to enter +the challenge is to have published a scientific article before 2010, in a +journal or a conference with proceedings, which contains results produced by +code, irrespectively of whether this code was published in some form at the +time or not.

    + +

    Note that we do not ask you to write a new version of your old code. We ask you +instead to try to make your old code to run on modern hardware/software +(with minimal modifications) in order to check if you can obtain the exact same +results that were published at least ten years ago.

    + +

    Sounds easy? We have good reasons to think this might be more difficult than you +think. And maybe the first problem you’ll have to solve is to find your own source +code.

    + +

    More information at: rescience.github.io/ten-years

    + + +
    • + + +
+ + +
+ +
+ +
+
+ + + + + + + diff --git a/index.md b/index.md deleted file mode 100644 index 2b4faf1..0000000 --- a/index.md +++ /dev/null @@ -1,39 +0,0 @@ ---- -layout: index ---- - -## Reproducible Science is good. Replicated Science is better. - -Re**Science** is a peer-reviewed journal that targets computational research -and encourages the explicit [replication](faq) of already published research, -promoting new and open-source implementations in order to ensure that the -original research is [reproducible](faq). - -To achieve this goal, the whole publishing chain is radically different from -other traditional scientific journals. Re**Science** lives on -[GitHub](https://github.com/ReScience/) where each new implementation of a -computational study is made available together with comments, explanations and -tests. Each submission takes the form of a pull request that is publicly -reviewed and tested in order to guarantee that any researcher can re-use it. If -you ever replicated computational results from the literature in your research, -Re**Science** is the perfect place to publish your new implementation. - -Re**Science** is collaborative by design. Everything can be forked and -modified. Don't hesitate to [write a submission](write), [join us](faq) and -to [become a reviewer](https://github.com/ReScience/ReScience/issues/27). - - -### Current activity - -Published articles: [22](https://github.com/ReScience/ReScience) -Submitted articles awaiting review: 0 -Articles currently under review: 2 ([#39], [#50]) -Articles awaiting publication: 0 -**Replication rate: 100%** - -[#39]: https://github.com/ReScience/ReScience-submission/pull/39 -[#50]: https://github.com/ReScience/ReScience-submission/pull/50 - - -## Latest News - diff --git a/news/2015/08/10/ReviewTest.html b/news/2015/08/10/ReviewTest.html new file mode 100644 index 0000000..dbf611c --- /dev/null +++ b/news/2015/08/10/ReviewTest.html @@ -0,0 +1,113 @@ + + + + + + + + + + + + Review process test is over + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

Review process test is over

+

Aug 10, 2015

+
+ +
+

We’ve been testing the +review process with +Tiziano Zito (editor), Benoît Girard (reviewer) and Mehdi Khamassi +(reviewer). They helped smoothing the whole process and we’re ready for mass +production! But let’s wait for a second review…

+ +
+ +
+ +
+
+ + + + + + + diff --git a/news/2015/09/01/journal-start.html b/news/2015/09/01/journal-start.html new file mode 100644 index 0000000..0e24f35 --- /dev/null +++ b/news/2015/09/01/journal-start.html @@ -0,0 +1,113 @@ + + + + + + + + + + + + Official creation + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

Official creation

+

Sep 1, 2015

+
+ +
+

It’s our great pleasure to announce the creation of ReScience which is a +peer-reviewed journal that targets computational research and encourages the +explicit replication of already published research, promoting new and +open-source implementations in order to ensure that the original research is +reproducible.

+ +
+ +
+ +
+
+ + + + + + + diff --git a/news/2015/09/06/LabCritics.html b/news/2015/09/06/LabCritics.html new file mode 100644 index 0000000..0a1f328 --- /dev/null +++ b/news/2015/09/06/LabCritics.html @@ -0,0 +1,110 @@ + + + + + + + + + + + + ReScience: A Scientific Journal Living on Github + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

ReScience: A Scientific Journal Living on Github

+

Sep 6, 2015

+
+ +
+

LabCritics kindly made a post introducing ReScience and explaining its goals: “Computational research is set to get new open source journal solely for publishing implementations of algorithms and codes already published. Termed ReScience (Replicated Science – I guess [note: yes]), the journal uses and exists solely on Github, a popular Web-based Git repository service, offering all of the distributed revision control and source code management functionality of Git.”

+ + +
+ +
+ +
+
+ + + + + + + diff --git a/news/2016/01/07/NewYear.html b/news/2016/01/07/NewYear.html new file mode 100644 index 0000000..54590a1 --- /dev/null +++ b/news/2016/01/07/NewYear.html @@ -0,0 +1,113 @@ + + + + + + + + + + + + New year, new challenges ahead + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

New year, new challenges ahead

+

Jan 7, 2016

+
+ +
+

Even though open and reproducible science is gaining fast ground, there still +exists a large number of published computational researches that are just +awaiting replication. Why not pick your favorite paper and try to replicate it +? If you’re interested in this specific paper, chances are that your replication +will also be interesting for a lot of researchers.

+ +
+ +
+ +
+
+ + + + + + + diff --git a/news/2016/07/02/Reviewers.html b/news/2016/07/02/Reviewers.html new file mode 100644 index 0000000..882084e --- /dev/null +++ b/news/2016/07/02/Reviewers.html @@ -0,0 +1,114 @@ + + + + + + + + + + + + You can help by becoming a reviewer + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

You can help by becoming a reviewer

+

Jul 2, 2016

+
+ +
+

ReScience is slowly gaining momentum and we currently have 4 submissions to +review. If you’re interested in helping ReScience and reproducibility, you can +become a reviewer. What you need is a github account, a one line description of +your expertise (see the Board for some +examples) and to tell us you’re interested such that we can add you to the board. You can also follow the submission repository and propose your help whenever a submission falls into your expertise domain.

+ + +
+ +
+ +
+
+ + + + + + + diff --git a/news/2016/10/19/Call-For-Replication.html b/news/2016/10/19/Call-For-Replication.html new file mode 100644 index 0000000..cbd8f2f --- /dev/null +++ b/news/2016/10/19/Call-For-Replication.html @@ -0,0 +1,120 @@ + + + + + + + + + + + + Call for replication + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

Call for replication

+

Oct 19, 2016

+
+ +
+

It is now possible to suggest an article for a replication. Just +open a new issue +in the +call for replication repository +and give the reference of the original article and possibly the reason you +would like to see this article replicated (please refrain from suggesting your +own work). Note that you’re also encouraged to register as a reviewer such that +you can review the replication you’ve been proposing if someone actually takes +up the challenge.

+ +

If you’re looking for some challenge, you can also look at the +current list of suggestions.

+ +
+ +
+ +
+
+ + + + + + + diff --git a/news/2017/12/18/ReScience-arXiv.html b/news/2017/12/18/ReScience-arXiv.html new file mode 100644 index 0000000..e5acd5f --- /dev/null +++ b/news/2017/12/18/ReScience-arXiv.html @@ -0,0 +1,134 @@ + + + + + + + + + + + + Sustainable computational science: the ReScience initiative + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

Sustainable computational science: the ReScience initiative

+

Dec 18, 2017

+
+ +
+

We just published our white paper on ReScience in +PeerJ

+ +

Abstract: Computer science offers a large set of tools for +prototyping, writing, running, testing, validating, sharing and reproducing +results; however, computational science lags behind. In the best case, authors +may provide their source code as a compressed archive and they may feel +confident their research is reproducible. But this is not exactly true. James +Buckheit and David Donoho proposed more than two decades ago that an article +about computational results is advertising, not scholarship. The actual +scholarship is the full software environment, code, and data that produced the +result. This implies new workflows, in particular in peer-reviews. Existing +journals have been slow to adapt: source codes are rarely requested and are +hardly ever actually executed to check that they produce the results advertised +in the article. ReScience is a peer-reviewed journal that targets computational +research and encourages the explicit replication of already published research, +promoting new and open-source implementations in order to ensure that the +original research can be replicated from its description. To achieve this goal, +the whole publishing chain is radically different from other traditional +scientific journals. ReScience resides on GitHub where each new implementation +of a computational study is made available together with comments, +explanations, and software tests.

+ +

References: N.P. Rougier et al., (2017) Sustainable computational science: the +ReScience initiative. PeerJ Computer Science 3:e142. DOI +doi.org/10.7717/peerj-cs.142

+ +
+ +
+ +
+
+ + + + + + + diff --git a/news/2019/05/23/Redesign.html b/news/2019/05/23/Redesign.html new file mode 100644 index 0000000..4326c60 --- /dev/null +++ b/news/2019/05/23/Redesign.html @@ -0,0 +1,120 @@ + + + + + + + + + + + + ReScience (R)evolution + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

ReScience (R)evolution

+

May 23, 2019

+
+ +
+

Four years ago, we launched ReScience, a new scientific journal aimed at +publishing the replication of existing computational research. Since ReScience +published its first article, things have been going steadily. We are still +alive, independent and without a budget. In the meantime, we have published +around 25 articles and the initial has grown from around 10 to roughly 100 +members (editors and reviewers), we have advertised ReScience at several +conferences worldwide, gave some interviews, and published an article +introducing ReScience in PeerJ Computer Science. Based on our experience at +managing the journal during these four years, we thought that time was ripe for +some changes. Read our +editorial if you want to +know more.

+ +
+ +
+ +
+
+ + + + + + + diff --git a/news/2019/10/11/TenYears.html b/news/2019/10/11/TenYears.html new file mode 100644 index 0000000..0bd493e --- /dev/null +++ b/news/2019/10/11/TenYears.html @@ -0,0 +1,134 @@ + + + + + + + + + + + + Ten Years Reproducibility Challenge + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ +
+

Ten Years Reproducibility Challenge

+

Oct 11, 2019

+
+ +
+

Did you ever try to run an old code that you wrote for a scientific article you +published years ago? Did you encounter any problems? Were you successful? We +are curious to hear your story. This is the reason why we are editing a special +issue of ReScience to collect these stories.

+ +

The ten years reproducibility challenge is an invitation for researchers to try +to run the code they’ve created for a scientific publication that was published +more than ten years ago. This code can be anything (statistical analysis, +numerical simulation, data processing, etc.), can be written in any language +and can address any scientific domain. The only mandatory condition to enter +the challenge is to have published a scientific article before 2010, in a +journal or a conference with proceedings, which contains results produced by +code, irrespectively of whether this code was published in some form at the +time or not.

+ +

Note that we do not ask you to write a new version of your old code. We ask you +instead to try to make your old code to run on modern hardware/software +(with minimal modifications) in order to check if you can obtain the exact same +results that were published at least ten years ago.

+ +

Sounds easy? We have good reasons to think this might be more difficult than you +think. And maybe the first problem you’ll have to solve is to find your own source +code.

+ +

More information at: rescience.github.io/ten-years

+ + +
+ +
+ +
+
+ + + + + + + diff --git a/news/index.html b/news/index.html new file mode 100644 index 0000000..547f440 --- /dev/null +++ b/news/index.html @@ -0,0 +1,271 @@ + + + + + + + + + + + + ReScience C + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ + + +
+

News

+ +
    + + +
  • +

    Ten Years Reproducibility Challenge + Oct 11, 2019

    +

    Did you ever try to run an old code that you wrote for a scientific article you +published years ago? Did you encounter any problems? Were you successful? We +are curious to hear your story. This is the reason why we are editing a special +issue of ReScience to collect these stories.

    + +

    The ten years reproducibility challenge is an invitation for researchers to try +to run the code they’ve created for a scientific publication that was published +more than ten years ago. This code can be anything (statistical analysis, +numerical simulation, data processing, etc.), can be written in any language +and can address any scientific domain. The only mandatory condition to enter +the challenge is to have published a scientific article before 2010, in a +journal or a conference with proceedings, which contains results produced by +code, irrespectively of whether this code was published in some form at the +time or not.

    + +

    Note that we do not ask you to write a new version of your old code. We ask you +instead to try to make your old code to run on modern hardware/software +(with minimal modifications) in order to check if you can obtain the exact same +results that were published at least ten years ago.

    + +

    Sounds easy? We have good reasons to think this might be more difficult than you +think. And maybe the first problem you’ll have to solve is to find your own source +code.

    + +

    More information at: rescience.github.io/ten-years

    + + +
    • + + + +
  • +

    ReScience (R)evolution + May 23, 2019

    +

    Four years ago, we launched ReScience, a new scientific journal aimed at +publishing the replication of existing computational research. Since ReScience +published its first article, things have been going steadily. We are still +alive, independent and without a budget. In the meantime, we have published +around 25 articles and the initial has grown from around 10 to roughly 100 +members (editors and reviewers), we have advertised ReScience at several +conferences worldwide, gave some interviews, and published an article +introducing ReScience in PeerJ Computer Science. Based on our experience at +managing the journal during these four years, we thought that time was ripe for +some changes. Read our +editorial if you want to +know more.

    + +
    • + + + +
  • +

    Sustainable computational science: the ReScience initiative + Dec 18, 2017

    +

    We just published our white paper on ReScience in +PeerJ

    + +

    Abstract: Computer science offers a large set of tools for +prototyping, writing, running, testing, validating, sharing and reproducing +results; however, computational science lags behind. In the best case, authors +may provide their source code as a compressed archive and they may feel +confident their research is reproducible. But this is not exactly true. James +Buckheit and David Donoho proposed more than two decades ago that an article +about computational results is advertising, not scholarship. The actual +scholarship is the full software environment, code, and data that produced the +result. This implies new workflows, in particular in peer-reviews. Existing +journals have been slow to adapt: source codes are rarely requested and are +hardly ever actually executed to check that they produce the results advertised +in the article. ReScience is a peer-reviewed journal that targets computational +research and encourages the explicit replication of already published research, +promoting new and open-source implementations in order to ensure that the +original research can be replicated from its description. To achieve this goal, +the whole publishing chain is radically different from other traditional +scientific journals. ReScience resides on GitHub where each new implementation +of a computational study is made available together with comments, +explanations, and software tests.

    + +

    References: N.P. Rougier et al., (2017) Sustainable computational science: the +ReScience initiative. PeerJ Computer Science 3:e142. DOI +doi.org/10.7717/peerj-cs.142

    + +
    • + + +
+ +

Archives

+ + + +
+ +
+ +
+
+ + + + + + + diff --git a/platform/index.html b/platform/index.html new file mode 100644 index 0000000..616fbf2 --- /dev/null +++ b/platform/index.html @@ -0,0 +1,203 @@ + + + + + + + + + + + + ReScience C + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ + + +
+

Provide platform information

+ +

Submissions to ReScience come with code. We ask information about the platform that was used +to run the code, the detail depending on the tools and programming languages used.

+ +

This information will be included in the file code/README.md of the submission. Consider +the whole execution pipeline for your results for possible additional tools (e.g. Bash, +random number generator, etc).

+ +

Version information for Python

+ +

For Python, NumPy, SciPy and matplotlib (common Python dependencies), the +following script will provide detailed information on your platform.

+ +
from __future__ import print_function
+import sys
+import platform
+
+print("Platform:", sys.platform)
+print("Python:", sys.version)
+print("Machine and architecture", platform.machine(), *platform.architecture())
+
+try:
+    import numpy as np
+    print("NumPy:", np.version.version)
+except:
+    pass
+
+try:
+    import scipy
+    print("SciPy:", scipy.version.version)
+except:
+    pass
+
+try:
+    import matplotlib
+    print("matplotlib:", matplotlib.__version__)
+except:
+    pass
+
+ +

The output, for instance

+ +
Platform: linux
+Python: 3.5.2+ (default, Sep 22 2016, 12:18:14) 
+[GCC 6.2.0 20160914]
+Machine and architecture x86_64 64bit ELF
+NumPy: 1.12.0
+SciPy: 0.18.1
+matplotlib: 2.0.0
+
+ +

Note that the versions of NumPy, SciPy and matplotlib should be given if they are used only +and that the version of any other library that is not part of Python’s standard library +should also be given.

+ +

Version information for compiled languages

+ +

For compiled languages, the important information consists in the platform, the +compiler, its version, and the compiler flags.

+ +

We provide below an example for the C language on Unix-like platforms. Modify it to suit +your project and feel free to contact ReScience via the GitHub issues or Twitter if you need +further assistance.

+ +

Platform information:

+ +
uname -mosv
+
+ +
Linux #1 SMP Debian 3.16.7-ckt9-3 (2015-04-23) x86_64 GNU/Linux
+
+ +

Hardware information:

+
grep -E '(^model name|^vendor_id|^flags)' /proc/cpuinfo  | sort | uniq
+
+ +
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm ida arat epb xsaveopt pln pts dtherm tpr_shadow vnmi flexpriority ept vpid fsgsbase smep erms
+model name      : Intel(R) Core(TM) i5-3230M CPU @ 2.60GHz
+vendor_id       : GenuineIntel
+
+ +

Compiler information for C:

+
gcc --version
+
+ +
gcc (Debian 6.2.0-5) 6.2.0 20160927
+Copyright (C) 2016 Free Software Foundation, Inc.
+This is free software; see the source for copying conditions.  There is NO
+warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+
+ +

with compilation flags -O3 -std=c99.

+ + +
+ +
+ +
+
+ + + + + + + diff --git a/publish.sh b/publish.sh new file mode 100755 index 0000000..97ba034 --- /dev/null +++ b/publish.sh @@ -0,0 +1,67 @@ +#! /bin/bash + +TGT_BRANCH=master # Branch containing the static website +SRC_BRANCH=sources # Branch containing source files for the website +CURRENT_BRANCH=$(git rev-parse --abbrev-ref HEAD) +BUILD_DIR=$(mktemp -d) + + +# Switch to sources branch +echo -n "Switching to source branch ($SRC_BRANCH)... " +if ! git checkout -q $SRC_BRANCH; then + echo "failed" + exit 0 +fi +echo "success" + + +# Check if there are any pending changes +echo -n "Checking repository status... " +if [ -n "$(git status --untracked-files=no --porcelain)" ]; then + echo "dirty" + echo " → Please commit pending changes before publishing." + exit 0 +fi +echo "clean" + + +# Repository is clean we can proceed +COMMIT_DATE=$(git log --pretty=format:'%cd' -n 1) +COMMIT_HASH=$(git log --pretty=format:'%h' -n 1) +echo "Commit to be published: $COMMIT_HASH ($COMMIT_DATE)" + + +# Website building +echo "Building static website" +bundle exec jekyll build -d $BUILD_DIR +if ! [ -d "$BUILD_DIR" ]; then + echo "Building has failed, aborting." + exit 0 +fi +echo "" + +# Switch to target branch +echo -n "Switching to target branch ($TGT_BRANCH)... " +if ! git checkout -q $TGT_BRANCH; then + echo "failed" + exit 0 +fi +echo "success" + + +# Publishing +echo -n "Publishing... " +ls | xargs rm -r +mv $BUILD_DIR/* . +git add . +git commit -q -m "Publishing from sources branch, commit $COMMIT_HASH ($COMMIT_DATE)" +if git push -q origin master; then + echo "success" +else + echo "failed" +fi +echo "" + +# Cleanup +git checkout -q $CURRENT_BRANCH +rm -rf $BUILD_DIR diff --git a/read/index.html b/read/index.html new file mode 100644 index 0000000..15c39a4 --- /dev/null +++ b/read/index.html @@ -0,0 +1,17937 @@ + + + + + + + + + + + + ReScience C + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ + + +
+

Contents

+ + + +

Under review

+ +

See https://github.com/ReScience/submissions/issues

+ +

Volume 11 (2026)

+ +

Issue 1

+
  1. + + + + + Replication + + in Machine Learning + + (Python) + + + + + + + + | 10.5281/zenodo.18401497 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hudovernik, V., Rot, Ž., Vovk, K., Škodnik, L., and Zajc, L.Č. 2026. Learning with Noisy Labels [ Re]visited. ReScience C 11, 1, #2. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computer Graphics + + (Python) + + + + + + + + | 10.5281/zenodo.18400484 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Perazzo, D., Castro, D.G.N.S., Velho, L., and Figueiredo, L.H. de. 2026. [Re] Curve-Fitting with Piecewise Parametric Cubics. ReScience C 11, 1, #1. +
    +
    + + + +
+ +

Volume 10 (2025)

+ +

Issue 1

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.16529268 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Reynes, M. and Aussel, A. 2025. [Re] Model of thalamocortical slow-wave sleep oscillations and transitions to activated states. ReScience C 10, 1, #5. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Artificial Intelligence + + (Python) + + + + + + + + | 10.5281/zenodo.16374814 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Belitsky, M., Laitenberger, F., Sheremet, D., and Belkacemi, N. 2025. [Re] Learning Fair Graph Representations via Automated Data Augmentations. ReScience C 10, 1, #6. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computer Science + + (Python) + + + + + + + + | 10.5281/zenodo.15321683 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Obadage, R.R., Thennakoon, K., Rajtmajer, S.M., and Wu, J. 2025. [Re] Network Deconvolution. ReScience C 10, 1, #4. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.15172014 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Casco-Rodriguez, J., Kemere, C., and Baraniuk, R.G. 2025. [Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models. ReScience C 10, 1, #3. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Machine Learning + + (Python) + + + + + + + + | 10.5281/zenodo.14964875 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Maheshwari, D. 2025. [Re] BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning. ReScience C 10, 1, #2. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in Machine Learning + + (Python) + + + + + + + + | 10.5281/zenodo.14953654 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Wagner, S.D., Kurowski, Y.P., Holländer, L.M., and Uelwer, T. 2025. [Re] When Does Label Smoothing Help? ReScience C 10, 1, #1. +
    +
    + + + +
+ +

Volume 9 (2023)

+ +

Issue 1

+
  1. + + + + + Replication + + in ecology + + (R) + + + + + + + + | 10.5281/zenodo.10371655 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Doyen, G., Picoche, C., and Barraquand, F. 2023. [Re] Biodiversity of plankton by species oscillations and chaos. ReScience C 9, 1, #4. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.10257800 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Lima, V., Shimoura, R.O., Kamiji, N.L., Battaglia, D., and Roque, A.C. 2023. [Re] Inter-areal Balanced Amplification Enhances Signal Propagation in a Large-Scale Circuit Model of the Primate Cortex. ReScience C 9, 1, #3. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Education Policy + + (Python) + + + + + + + + | 10.5281/zenodo.10255347 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Allard, T., Béziaud, L., and Gambs, S. 2023. [ Re]Simulating socioeconomic-based affirmative action. ReScience C 9, 1, #2. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Computer Vision + + (Python) + + + + + + + + | 10.5281/zenodo.7800679 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Lemmens, J., Jancura, P., Dubbelman, G., and Elrofai, H. 2023. [Re] Object Detection Meets Knowledge Graphs. ReScience C 9, 1, #1. +
    +
    + + + +
+ +

Issue 2

+
  1. + + + + + Editorial + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8200058 + + + + + | PDF + + + + + + + + + + + + + + +| BibTeX +
    +     + + + +Sinha, K., Bleeker, M., Bhargav, S., et al. 2023. ML Reproducibility Challenge 2022. ReScience C 9, 2, #46. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173652 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Erkol, M., Kınlı, F., Özcan, B., and Kıraç, F. 2023. [Re] Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization. ReScience C 9, 2, #2. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173654 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +McLeish, S. and Tran-Thanh, L. 2023. [Re] End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. ReScience C 9, 2, #3. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173656 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Langezaal, E.R., Belleman, J., Veenboer, T., and Noorthoek, J. 2023. [Re] Label-Free Explainability for Unsupervised Models. ReScience C 9, 2, #4. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173658 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Brivio, M. and Çöltekin, Ç. 2023. [Re] Exploring the Representation of Word Meanings in Context. ReScience C 9, 2, #5. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173662 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Marini, L., Nabeel, M., and Loiko, A. 2023. [Re] Intriguing Properties of Contrastive Losses. ReScience C 9, 2, #6. +
    +
    + + + +
    7. +
  7. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173664 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Žontar, L. 2023. [Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization. ReScience C 9, 2, #7. +
    +
    + + + +
    8. +
  8. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (python, bash) + + + + + + + + | 10.5281/zenodo.8173666 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Yuan, J. and Le-Phuoc, D. 2023. [Re] Hypergraph-Induced Semantic Tuplet Loss for Deep Metric Learning. ReScience C 9, 2, #8. +
    +
    + + + +
    9. +
  9. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173668 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Špendl, M. and Pirc, K. 2023. [Re] Easy Bayesian Transfer Learning with Informative Priors. ReScience C 9, 2, #9. +
    +
    + + + +
    10. +
  10. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173672 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Dubbeldam, E., Eijpe, A., Ruthardt, J., and Sasse, R. 2023. [Re] On the Reproducibility of CartoonX. ReScience C 9, 2, #10. +
    +
    + + + +
    11. +
  11. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173674 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Pariza, V., Pal, A., Pawar, M., and Faber, Q.S. 2023. [Re] Reproducibility Study of “Label-Free Explainability for Unsupervised Models.” ReScience C 9, 2, #11. +
    +
    + + + +
    12. +
  12. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173678 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Morita, K. 2023. [Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles. ReScience C 9, 2, #12. +
    +
    + + + +
    13. +
  13. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173680 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Buchner, V.L., Schutte, P.O.O., Allal, Y.B., and Ahadi, H. 2023. [Re] Fairness Guarantees under Demographic Shift. ReScience C 9, 2, #13. +
    +
    + + + +
    14. +
  14. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173682 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Camara, P., Kloos, M., Kyrmanidi, V., Kluska, A., Terlou, R., and Krause, L. 2023. [Re] DialSummEval - Evaluation of automatic summarization evaluation metrics. ReScience C 9, 2, #14. +
    +
    + + + +
    15. +
  15. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173686 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Don, M., Chatterji, S., Kapralova, M., and Amaudruz, R. 2023. [Re] On the Reproducibility of "FairCal: Fairness Calibration for Face Verification". ReScience C 9, 2, #15. +
    +
    + + + +
    16. +
  16. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173688 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Garcarz, S., Giorkatzi, A., Ivășchescu, A., and Pîslar, T.-M. 2023. [Re] Reproducibility Study: Label-Free Explainability for Unsupervised Models. ReScience C 9, 2, #16. +
    +
    + + + +
    17. +
  17. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173692 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Martorella, T., Contreras, H.M.R., and García, D.C. 2023. [Re] Numerical influence of ReLU’(0) on backpropagation. ReScience C 9, 2, #17. +
    +
    + + + +
    18. +
  18. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8206607 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Agafonov, D., Matthijsse, J., Nonkes, N., and Sande, Z. van de. 2023. [¬Re] A Reproducibility Case Study of “Fairness Guarantees under Demographic Shift.” ReScience C 9, 2, #18. +
    +
    + + + +
    19. +
  19. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173696 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mohorčič, D. and Ocepek, D. 2023. [Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods. ReScience C 9, 2, #19. +
    +
    + + + +
    20. +
  20. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173698 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hu, A., Ranum, O., Pozrikidou, C., and Zhou, M. 2023. [Re] Reproducibility study of Joint Multisided Exposure Fairness for Recommendation. ReScience C 9, 2, #20. +
    +
    + + + +
    21. +
  21. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173703 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Türk, M., Busser, L., Dijk, D. van, and Bosch, M.J.A. 2023. [Re] Exploring the Explainability of Bias in Image Captioning Models. ReScience C 9, 2, #21. +
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    22. +
  22. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (python) + + + + + + + + | 10.5281/zenodo.8173705 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bikker, D., Kleuver, G. de, Hu, W., and Veenman, B. 2023. [¬Re] Reproducibility study of ‘Proto2Proto: Can you recognize the car, the way I do?’ ReScience C 9, 2, #22. +
    +
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    23. +
  23. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173707 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Simoncini, W., Gogou, I., Lopes, M.F., and Kremer, R. 2023. [Re] Reproducibility Study of ”Focus On The Common Good: Group Distributional Robustness Follows.” ReScience C 9, 2, #23. +
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  24. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (python) + + + + + + + + | 10.5281/zenodo.8173711 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Papp, G., Wagenbach, J., Vries, L.J. de, and Mather, N. 2023. [Re] Reproducibility study of ”Label-Free Explainability for Unsupervised Models.” ReScience C 9, 2, #24. +
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    25. +
  25. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173713 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Buis, E., Dijkstra, S., and Heijermans, B. 2023. [Re] Reproducibility study of “Explaining Deep Convolutional Neural Networks via Latent Visual-Semantic Filter Attention.” ReScience C 9, 2, #25. +
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    26. +
  26. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173715 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Baratov, F., Yüksel, G., Petcu, D., and Bakker, J. 2023. [Re] Reproducibility Study of "Quantifying Societal Bias Amplification in Image Captioning". ReScience C 9, 2, #26. +
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    27. +
  27. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173717 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Zila, E., Gerbscheid, J., Sträter, L., and Kretschmar, K. 2023. [Re] On the reproducibility of "CrossWalk: Fairness-Enhanced Node Representation Learning". ReScience C 9, 2, #27. +
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    28. +
  28. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173719 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Greven, J., Stallinga, S., and Seljee, Z. 2023. [Re] Reproducing FairCal: Fairness Calibration for Face Verification. ReScience C 9, 2, #28. +
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    29. +
  29. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173721 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Taslimi, S., Foeng, L.C.A., Kayal, P., Patra, A.P., and Patra, A.P. 2023. [Re] Reproducibility Study of ’CartoonX: Cartoon Explanations of Image Classifiers.’ ReScience C 9, 2, #29. +
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    30. +
  30. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173725 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Merk, D., Smit, D., Beukers, B., and Mendsuren, T. 2023. [Re] Reproducibility Study of ”Latent Space Smoothing for Individually Fair Representations.” ReScience C 9, 2, #30. +
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    31. +
  31. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173729 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Aillet, A. and Sondén, S. 2023. [Re] Variational Neural Cellular Automata. ReScience C 9, 2, #31. +
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    32. +
  32. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (python) + + + + + + + + | 10.5281/zenodo.8173733 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Benmerzoug, A. and Benito Delgado, M. de. 2023. [Re] If you like Shapley, then you’ll love the core. ReScience C 9, 2, #32. +
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    33. +
  33. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173735 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Livernoche, V. and Sujaya, V. 2023. [Re] A Reproduction of Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification. ReScience C 9, 2, #33. +
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    34. +
  34. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173737 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Cordaro, D., Cox, S., Ren, Y., and Yu, T. 2023. [¬Re] G-Mixup: Graph Data Augmentation for Graph Classification. ReScience C 9, 2, #34. +
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    35. +
  35. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173739 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bose, P., Pandey, C.S., and Fund, F. 2023. [Re] Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate Speech Classification. ReScience C 9, 2, #35. +
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    36. +
  36. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173741 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Antequera, P., Gonzalez, E., Grasa, M., and Raaphorst, M. van. 2023. [Re] RELIC: Reproducibility and Extension on LIC metric in quantifying bias in captioning models. ReScience C 9, 2, #36. +
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    37. +
  37. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173745 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Kyrylov, V., Bedi, N.S., and Zang, Q. 2023. [Re] VAE Approximation Error: ELBO and Exponential Families. ReScience C 9, 2, #37. +
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    38. +
  38. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173747 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Moens, G.J., Witte, J. de, Göbel, T.P., and Oever, M. van den. 2023. [Re] CrossWalk Fairness-enhanced Node Representation Learning. ReScience C 9, 2, #38. +
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    39. +
  39. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173749 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Pantea, L. and Blahovici, A. 2023. [Re] CrossWalk: Fairness-enhanced Node Representation Learning. ReScience C 9, 2, #39. +
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    40. +
  40. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173751 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Charisoudis, A., Huth, S.E. von, and Jansson, E. 2023. [Re] Masked Autoencoders Are Small Scale Vision Learners: A Reproduction Under Resource Constraints. ReScience C 9, 2, #40. +
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    41. +
  41. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173753 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mahlau, Y., Kayser, L., and Berg, L. 2023. [Re] On Explainability of Graph Neural Networks via Subgraph Explorations. ReScience C 9, 2, #41. +
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    42. +
  42. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python3) + + + + + + + + | 10.5281/zenodo.8173755 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Alexander, S., Ildus, S., and Evgeniy, S. 2023. [Re] "Towards Understanding Grokking". ReScience C 9, 2, #42. +
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    43. +
  43. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173757 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Moalla, S., Madeira, M., Riccio, L., and Lee, J. 2023. [Re] Reproducibility Study of Behavior Transformers. ReScience C 9, 2, #43. +
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    44. +
  44. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173759 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Sun, K., Williams, A., and Hupkes, D. 2023. [Re] A Replication Study of Compositional Generalization Works on Semantic Parsing. ReScience C 9, 2, #44. +
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    45. +
  45. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173763 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Lee, S.R. and Lee, S.B. 2023. [Re] Pure Noise to the Rescue of Insufficient Data. ReScience C 9, 2, #45. +
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  46. + + + + + Replication + + in ML Reproducibility Challenge 2022 + + (Python) + + + + + + + + | 10.5281/zenodo.8173650 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Omeragić, E. and Đuranović, V. 2023. [Re] G-Mixup: Graph Data Augmentation for Graph Classification. ReScience C 9, 2, #1. +
    +
    + + + +
+ +

Volume 8 (2022)

+ +

Issue 2 (ML Reproducibility Challenge 2021)

+
  1. + + + + + Editorial + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574723 + + + + + | PDF + + + + + + + + + + + + + + +| BibTeX +
    +     + + + +Sinha, K., Dodge, J., Luccioni, S., et al. 2022. ML Reproducibility Challenge 2021. ReScience C 8, 2, #48. +
    +
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    2. +
  2. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574625 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Ankit, A., Ambekar, S., Varadharajan, B., and Alence, M. 2022. [Re] Counterfactual Generative Networks. ReScience C 8, 2, #2. +
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    3. +
  3. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574629 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Ashok, A. and Aekula, H. 2022. [Re] Does Self-Supervision Always Improve Few-Shot Learning? ReScience C 8, 2, #3. +
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    4. +
  4. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574631 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Athanasiadis, I., Moschovis, G., and Tuoma, A. 2022. [Re] Weakly-Supervised Semantic Segmentation via Transformer Explainability. ReScience C 8, 2, #4. +
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    5. +
  5. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574635 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bagad, P., Hilders, P., Maas, J., and Goede, D. de. 2022. [Re] Reproducibility Study of “Counterfactual Generative Networks.” ReScience C 8, 2, #5. +
    +
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    6. +
  6. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574637 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Boer, S. de, Cosma, R.A., Knobel, L., Koishekenov, Y., and Shaffrey, B. 2022. [Re] Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling. ReScience C 8, 2, #6. +
    +
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    7. +
  7. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574639 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Brivio, M. and Çöltekin, Ç. 2022. [¬Re] Hate Speech Detection based on Sentiment Knowledge Sharing. ReScience C 8, 2, #7. +
    +
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    8. +
  8. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574641 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Burger, M., Burg, K. ter, Titarsolej, S., and Khan, S.J. 2022. [Re] Reproducibility Study - SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition. ReScience C 8, 2, #8. +
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    9. +
  9. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574643 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Buvanesh, A. and Panwar, M. 2022. [Re] AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients. ReScience C 8, 2, #9. +
    +
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    10. +
  10. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574645 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Dasu, V.A. and T.K., M.M. 2022. [Re] GANSpace: Discovering Interpretable GAN Controls. ReScience C 8, 2, #10. +
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    11. +
  11. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574647 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Drabent, K., Wijnja, S., Sluijter, T., and Bereda, K. 2022. [Re] Replication study of "Privacy-preserving Collaborative Learning". ReScience C 8, 2, #11. +
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    12. +
  12. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574649 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Džubur, B. 2022. [Re] A Cluster-based Approach for Improving Isotropy in Contextual Embedding Space. ReScience C 8, 2, #12. +
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    13. +
  13. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574651 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Eaton, E. and Naghavi, P. 2022. [Re] Reproduction and Extension of "Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation". ReScience C 8, 2, #13. +
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    14. +
  14. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574653 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Eijkelboom, F., Fokkema, M., Lau, A., and Verheijen, L. 2022. [Re] Reproduction Study of Variational Fair Clustering. ReScience C 8, 2, #14. +
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    15. +
  15. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574655 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Geijn, C. van de, Kyriacou, V., Papadopoulou, I., and Vasileiou, V. 2022. [Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace. None 8, 2, #15. +
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    16. +
  16. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574657 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hardy, I. 2022. [Re] An Implementation of Fair Robust Learning. ReScience C 8, 2, #16. +
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    17. +
  17. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574659 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Höppe, T., Miszkurka, A., and Wilkman, D.B. 2022. [Re] Understanding Self-Supervised Learning Dynamics without Contrastive Pairs. ReScience C 8, 2, #17. +
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    18. +
  18. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574661 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Jiles, R. and Chakraborty, M. 2022. [Re] Domain Generalization using Causal Matching. ReScience C 8, 2, #18. +
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    19. +
  19. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574663 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Kirca, I.-A., Hamerslag, D., Baas, A., and Prent, J. 2022. [¬Re] Reproducibility Study of ’Exacerbating Algorithmic Bias through Fairness Attacks’ . ReScience C 8, 2, #19. +
    +
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    20. +
  20. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574665 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Kolkman, G., Athmer, J., Labro, A., and Kulicki, M. 2022. [Re] Strategic classification made practical: reproduction. ReScience C 8, 2, #20. +
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    21. +
  21. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574667 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bosch, E., Ettes, R., Korporaal, D., and Meer, G. van. 2022. [Re] Replication study of ’Explaining in Style: Training a GAN to explain a classifier in StyleSpace.’ None 8, 2, #21. +
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    22. +
  22. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (python) + + + + + + + + | 10.5281/zenodo.6574669 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Tafuro, M., Lombardo, A., Veljković, T.H., and Becker-Czarnetzki, L. 2022. [Re] Exacerbating Algorithmic Bias through Fairness Attacks. ReScience C 8, 2, #22. +
    +
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    23. +
  23. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (R) + + + + + + + + | 10.5281/zenodo.6574671 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +De Luisa, A. 2022. [Re] Thompson Sampling for Bandits with Clustered Arms. ReScience C 8, 2, #23. +
    +
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    24. +
  24. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574673 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mast, D. van der, Haddou, S.B., Chu, J., and Stefels, J. 2022. [Re] Replication Study of "Fairness and Bias in Online Selection". None 8, 2, #24. +
    +
    + + + +
    25. +
  25. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574675 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Chen, A., Matsumoto, S., and Varma, R.S. 2022. [Re] Projection-based Algorithm for Updating the TruncatedSVD of Evolving Matrices. ReScience C 8, 2, #25. +
    +
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    26. +
  26. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574677 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mehta, A., Uppal, K., Jadhav, K., Natarajan, M., Agrawal, M., and Chakravarty, D. 2022. [Re] Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation. ReScience C 8, 2, #26. +
    +
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    27. +
  27. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574679 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mikler, S. 2022. [Re] Reproducibility Study: Comparing Rewinding and Fine-tuning in Neural Network Pruning. ReScience C 8, 2, #27. +
    +
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    28. +
  28. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574681 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Nalmpantis, A., Panagiotopoulos, A., Gkountouras, J., and Papakostas, K. 2022. [Re] Exacerbating Algorithmic Bias through Fairness Attacks. None 8, 2, #28. +
    +
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    29. +
  29. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574683 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Neplenbroek, V., Perdijk, S., and Prins, V. 2022. [Re] Replication study of ’Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling.’ ReScience C 8, 2, #29. +
    +
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    30. +
  30. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574685 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Galatolo, A. and Nilsson, A. 2022. [Re] Replicating and Improving GAN2Shape Through Novel Shape Priors and Training Steps. ReScience C 8, 2, #30. +
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    31. +
  31. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574687 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Panigrahi, S.S. and Patnaik, S. 2022. [Re] Value Alignment Verification. ReScience C 8, 2, #31. +
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    32. +
  32. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574689 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Petcu, R., Praat, P., Wijnen, J., and Rerres, M. 2022. [Re] Replication Study of "Fairness and Bias in Online Selection". ReScience C 8, 2, #32. +
    +
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    33. +
  33. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python 3) + + + + + + + + | 10.5281/zenodo.6574691 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Peters, N., Crosbie, J., Hull, R. vant́, and Strampel, M. 2022. [¬Re] Reproducing ’Fair Selective Classification via Sufficiency.’ None 8, 2, #33. +
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    34. +
  34. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574693 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Ranjan, R., Bhakta, H., Jha, A., and Maheshwari, P. 2022. [Re] Differentiable Spatial Planning using Transformers. ReScience C 8, 2, #34. +
    +
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    35. +
  35. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574695 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Rucks, N., Uelwer, T., and Harmeling, S. 2022. [Re] Solving Phase Retrieval With a Learned Reference. ReScience C 8, 2, #35. +
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    36. +
  36. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574697 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Sen, R., Sinha, S., Jha, A., and Maheshwari, P. 2022. [Re] Reproducibility Report: Contrastive Learning of Socially-aware Motion Representations. ReScience C 8, 2, #36. +
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    37. +
  37. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574699 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Shukla, A., Roy, S., Chawla, Y., et al. 2022. [Re] From goals, waypoints and paths to longterm human trajectory forecasting. ReScience C 8, 2, #37. +
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    38. +
  38. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574701 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Stropnik, V. and Oražem, M. 2022. [Re] Graph Edit Networks. ReScience C 8, 2, #38. +
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    39. +
  39. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574703 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Kljun, M., Teršek, M., and Vreš, D. 2022. [Re] Learning to count everything. ReScience C 8, 2, #39. +
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    40. +
  40. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574705 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Togt, J. van der, Tiyavorabun, L., Rosati, M., and Starace, G. 2022. [Re] Badder Seeds: Reproducing the Evaluation of Lexical Methods for Bias Measurement. ReScience C 8, 2, #40. +
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    41. +
  41. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python, Matlab) + + + + + + + + | 10.5281/zenodo.6574707 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Trojer, Ž. 2022. [Re] Transparent Object Tracking Benchmark. ReScience C 8, 2, #41. +
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    42. +
  42. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574709 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Vleuten, N. van der, Radusinović, T., Akkerman, R., and Reksoprodjo, M. 2022. [Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace. None 8, 2, #42. +
    +
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    43. +
  43. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574711 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Shulev, V., Verhagen, P., Wang, S., and Zhuge, J. 2022. [Re] Replication Study of DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks. ReScience C 8, 2, #43. +
    +
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    44. +
  44. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574713 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Warmerdam, A.T., Loerakker, L., Meijer, L., and Nissen, O. 2022. [Re] Privacy-preserving collaborative learning with automatic transformation search. ReScience C 8, 2, #44. +
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    45. +
  45. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574715 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Wilschut, R.I., Wiggers, T.P.A., Oort, R.S., and Orden, T.A. van. 2022. [Re] Robust Counterfactual Explanations on Graph Neural Networks. ReScience C 8, 2, #45. +
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    46. +
  46. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574719 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Yılmaz, D., Kınlı, F., Özcan, B., and Kıraç, F. 2022. [Re] Lifting 2D StyleGAN for 3D-Aware Face Generation. ReScience C 8, 2, #46. +
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    47. +
  47. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574721 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Zrimšek, U. 2022. [Re] Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction. ReScience C 8, 2, #47. +
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    48. +
  48. + + + + + Replication + + in ML Reproducibility Challenge 2021 + + (Python) + + + + + + + + | 10.5281/zenodo.6574623 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Ahmed, W. and Samuel, S. 2022. [Re] Nondeterminism and Instability in Neural Network Optimization. ReScience C 8, 2, #1. +
    +
    + + + +
+ +

Issue 1

+
  1. + + + + + Replication + + in Social Psychology + + (Python) + + + + + + + + | 10.5281/zenodo.7484072 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Wallrich, L. 2022. [Re] Groups of diverse problem-solvers outperform groups of highest-ability problem-solvers - most of the time. ReScience C 8, 1, #6. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Biological Computing + + (Octave) + + + + + + + + | 10.5281/zenodo.6801765 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Sant’Anna, G.B. de and Costa, M.F. 2022. [Re] A Multi-Functional Synthetic Gene Network. ReScience C 8, 1, #5. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.6573684 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Misiek, T. and Khamassi, M. 2022. [Re] A general model of hippocampal and dorsal striatal learning and decision making. ReScience C 8, 1, #4. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Ecology + + (C++) + + + + + + + + | 10.5281/zenodo.6546488 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Picoche, C., Young, W.R., and Barraquand, F. 2022. [Re] Reproductive pair correlations and the clustering of organisms. ReScience C 8, 1, #3. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | https://doi.org/10.5281/zenodo.6484021 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Gillard, T., Fix, J., and Dutech, A. 2022. [Re] Modeling habits as self-sustained patterns of sensorimotor behavior. ReScience C 8, 1, #2. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in Computer Science + + (Python) + + + + + + + + | 10.5281/zenodo.6255131 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Maurel, D., Fillioux, J., and Gugenheim, D. 2022. [Re] Effective Program Debloating via Reinforcement Learning. ReScience C 8, 1, #1. +
    +
    + + + +
+ +

Volume 7 (2021)

+ +

Issue 2 (ML Reproducibility Challenge 2020)

+
  1. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4835602 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Verma, R., Wagemans, J.J.O., Dahal, P., and Elfrink, A. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #24. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4833219 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Albanis, G., Zioulis, N., Chatzitofis, A., Dimou, A., Zarpalas, D., and Daras, P. 2021. [Re] On end-to-end 6DoF object pose estimation and robustness to object scale. ReScience C 7, 2, #2. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (python) + + + + + + + + | 10.5281/zenodo.4833389 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Arvind, M. and Mama, M. 2021. [Re] Neural Networks Fail to Learn Periodic Functions and How to Fix It. ReScience C 7, 2, #3. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (python) + + + + + + + + | 10.5281/zenodo.4833547 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Teule, T., Reints, N., Gerges, C.A., and Baanders, P. 2021. [Re] Deep Fair Clustering for Visual Learning. ReScience C 7, 2, #4. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4833681 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Garg, P., Singhal, L., and Sardana, A. 2021. [Re] Training Binary Neural Networks using the Bayesian Learning Rule. ReScience C 7, 2, #5. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python 3) + + + + + + + + | 10.5281/zenodo.4834146 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Habacker, R., Harrison, A., Parisot, M., and Snijders, A. 2021. [Re] Reproducing Learning to Deceive With Attention-Based Explanations. ReScience C 7, 2, #6. +
    +
    + + + +
    7. +
  7. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (English) + + + + + + + + | 10.5281/zenodo.4834242 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Holdijk, L., Boon, M., Henckens, S., and Jong, L. de. 2021. [Re] Parameterized Explainer for Graph Neural Network. ReScience C 7, 2, #7. +
    +
    + + + +
    8. +
  8. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4834352 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Kim, S.S.Y., Zhang, S., Meister, N., and Russakovsky, O. 2021. [Re] Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias. ReScience C 7, 2, #8. +
    +
    + + + +
    9. +
  9. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4834442 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Li, C., Tu, R., and Zhang, H. 2021. [Re] Reimplementation of FixMatch and Investigation on Noisy (Pseudo) Labels and Confirmation Errors of FixMatch. ReScience C 7, 2, #9. +
    +
    + + + +
    10. +
  10. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4834516 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Liiv, T., Lennelöv, E., and Norén, A. 2021. [Re] A Reproduction of Ensemble Distribution Distillation. ReScience C 7, 2, #10. +
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    11. +
  11. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4834610 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Stephen, K. and Menon, V. 2021. [Re] Learning Memory Guided Normality for Anomaly Detection. ReScience C 7, 2, #11. +
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    12. +
  12. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4834672 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Menteş, S., Kınlı, F., Özcan, B., and Kıraç, F. 2021. [Re] Spatial-Adaptive Network for Single Image Denoising. ReScience C 7, 2, #12. +
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    + + + +
    13. +
  13. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4834744 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mizrahi, D., Yüksel, O.K., and Kyzy, A.M. 2021. [Re] Can gradient clipping mitigate label noise? ReScience C 7, 2, #13. +
    +
    + + + +
    14. +
  14. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (python) + + + + + + + + | 10.5281/zenodo.4834856 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Kireev, K., Mohtashami, A., and Pajouheshgar, E. 2021. [Re] Warm-Starting Neural Network Training. ReScience C 7, 2, #14. +
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    15. +
  15. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4834942 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +P, J.J. and Sardana, A. 2021. [Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings. ReScience C 7, 2, #15. +
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    16. +
  16. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4835056 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Reijnaers, D.J.W., Pavert, D.B. van de, Scheuer, G., and Huang, L. 2021. [Re] Explaining Groups of Points in Low-Dimensional Representations. ReScience C 7, 2, #16. +
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    17. +
  17. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python 3) + + + + + + + + | 10.5281/zenodo.4839595 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Deprez, H.L. gezegd, Rijsdijk, G., Rooij, B. de, and Zwerink, W. 2021. [Re] Reproducing ’Identifying through flows for recovering latent representations.’ ReScience C 7, 2, #17. +
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    18. +
  18. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4835278 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Balsells Rodas, C., Canal Anton, O., and Taschin, F. 2021. [Re] Hamiltonian Generative Networks. ReScience C 7, 2, #18. +
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    19. +
  19. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (python) + + + + + + + + | 10.5281/zenodo.4835356 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + + +| BibTeX +
    +     + + + +Schneider, M. and Körner, M. 2021. [Re] Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention. ReScience C 7, 2, #19. +
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    20. +
  20. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4835431 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Sheverdin, A., Knijff, A., Corten, N., and Lange, G. 2021. [Re] Reproducibility report of "Interpretable Complex-Valued Neural Networks for Privacy Protection". ReScience C 7, 2, #20. +
    +
    + + + +
    21. +
  21. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4835564 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Sundar, V. and Dwaraknath, R.V. 2021. [Re] Rigging the Lottery: Making All Tickets Winners. ReScience C 7, 2, #21. +
    +
    + + + +
    22. +
  22. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (Python) + + + + + + + + | 10.5281/zenodo.4835592 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bouwman, P., Li, Y., Weerd, R. van der, and Verhoef, F. 2021. [Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency? ReScience C 7, 2, #22. +
    +
    + + + +
    23. +
  23. + + + + + Replication + + in ML Reproducibility Challenge 2020 + + (python) + + + + + + + + | 10.5281/zenodo.4835600 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Verhoeven, I., Chen, X., Hu, Q., and Holubar, M. 2021. [Re] Replication Study of ’Generative causal explanations of black-box classifiers.’ ReScience C 7, 2, #23. +
    +
    + + + +
    24. +
  24. + + + + + Editorial + + + + + + + | 10.5281/zenodo.4833117 + + + + + | PDF + + + + + + + + + + + + + + +| BibTeX +
    +     + + + +Sinha, K., Dodge, J., Luccioni, S., Forde, J.Z., Stojnic, R., and Pineau, J. 2021. ML Reproducibility Challenge 2020. ReScience C 7, 2, #1. +
    +
    + + + +
+ +

Issue 1

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.5718075 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Sankar, R., Thou, N., Rougier, N.P., and Leblois, A. 2021. [Re] A Reservoir Computing Model of Reward-Modulated Motor Learning and Automaticity. ReScience C 7, 1, #11. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computational Biology + + (Julia) + + + + + + + + | 10.5281/zenodo.5722853 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Dhane, F., Soeharjono, S., Stern, K., MacDonald, A., and Poisot, T. 2021. [Re] The Evolution of Virulence in Pathogens with Vertical and Horizontal Transmission. ReScience C 7, 1, #10. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neuroscience + + (Python and Brian 2) + + + + + + + + | 10.5281/zenodo.5657320 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Carvalho, T.T.A., Domingos, L.B., Shimoura, R.O., et al. 2021. [Re] Context-Dependent Encoding of Fear and Extinction Memories in a Large-Scale Network Model of the Basal Amygdala. ReScience C 7, 1, #9. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.5379631 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Paul, T.E. and Bourdenx, M. 2021. [Re] Spread of alpha-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis. ReScience C 7, 1, #8. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Computational Fluid Dynamics + + (C++) + + + + + + + + | 10.5281/zenodo.5234931 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mesnard, O. and Barba, L.A. 2021. [Re] Three-dimensional wake topology and propulsive performance of low-aspect-ratio pitching-rolling plates. ReScience C 7, 1, #7. +
    +
    + + + +
    6. +
  6. + + + + + Editorial + + + + + + + | 10.5281/zenodo.5217602 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Varma, M. and Prabhu, N. 2021. [Re] On the Relationship between Self-Attention and Convolutional Layers. ReScience C 7, 1, #6. +
    +
    + + + +
    7. +
  7. + + + + + Replication + + in Ecology + + (R) + + + + + + + + | 10.5281/zenodo.5006005 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + + +| BibTeX +
    +     + + + +Boersch-Supan, P.H. 2021. [Re] Modeling Insect Phenology Using Ordinal Regression and Continuation Ratio Models. ReScience C 7, 1, #5. +
    +
    + + + +
    8. +
  8. + + + + + Replication + + in Algorithmics + + (C++) + + + + + + + + | 10.5281/zenodo.4836230 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Lécuyer, F., Danisch, M., and Tabourier, L. 2021. [Re] Speedup Graph Processing by Graph Ordering. ReScience C 7, 1, #3. +
    +
    + + + +
    9. +
  9. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.4655870 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Boraud, T. and Strock, A. 2021. [Re] A Neurodynamical Model for Working Memory. ReScience C 7, 1, #1. +
    +
    + + + +
    10. +
  10. + + + + + Replication + + in Game Theory + + (Python 3) + + + + + + + + | 10.5281/zenodo.4646680 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Geoffroy, F. 2021. [Re] Assortative matching and search. ReScience C 7, 1, #2. +
    +
    + + + +
+ +

Volume 6 (2020)

+ +

Issue 3

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.4461767 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Torre-Ortiz, C. de la and Nioche, A. 2021. [Re] Neural Network Model of Memory Retrieval. ReScience C 6, 3, #8. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Reinforcement Learning + + (python) + + + + + + + + | 10.5281/zenodo.4242943 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Brückner, L. and Nioche, A. 2020. [Re] Faster Teaching via POMDP Planning. ReScience C 6, 3, #7. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neuroscience + + (Julia) + + + + + + + + | 10.5281/zenodo.4139359 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Davies, I. and Eglen, S. 2020. [Re] The principal components of natural images. ReScience C 6, 3, #6. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Ecology + + (julia) + + + + + + + + | 10.5281/zenodo.4022518 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Dansereau, G., Banville, F., Basque, E., MacDonald, A., and Poisot, T. 2020. [Re] Chaos in a Three-Species Food Chain. ReScience C 6, 3, #5. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Neuroscience + + (Matlab) + + + + + + + + | 10.5281/zenodo.4022361 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hentschke, H. 2020. [Re] Hippocampal Phase-Amplitude Coupling unearthed again. ReScience C 6, 3, #3. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in Computer Science + + + + + + + + | 10.5281/zenodo.3885793 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mahmoudian, S. 2020. [Re] Measures for investigating the contextual modulation of information transmission. ReScience C 6, 3, #2. +
    +
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    7. +
  7. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.3842360 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Upshall, M. and Shifman, A.R. 2020. [Re] Mathematical analysis of depolarization block mediated by slow inactivation of fast sodium channels in midbrain dopamine neurons. ReScience C 6, 3, #1. +
    +
    + + + +
+ +

Issue 2 (NeurIPS 2019 Reproducibility Challenge)

+
  1. + + + + + Editorial + + + + + + + | 10.5281/zenodo.3818627 + + + + + | PDF + + + + + + + + + + + + + + +| BibTeX +
    +     + + + +Sinha, K., Pineau, J., Forde, J., Ke, R.N., and Larochelle, H. 2020. NeurIPS 2019 Reproducibility Challenge. ReScience C 6, 2, #11. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818607 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Nayak, N., Raj, V., and Kalyani, S. 2020. [Re] A comprehensive study on binary optimizer and its applicability. ReScience C 6, 2, #9. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818609 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Matosevic, A., Hein, E., and Nuzzo, F. 2020. [Re] Generative Modeling by Estimating Gradients of the Data Distribution. ReScience C 6, 2, #8. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818613 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Liljefors, F., Sorkhei, M., and Broomé, S. 2020. [Re] Unsupervised Scalable Representation Learning for Multivariate Time Series. ReScience C 6, 2, #6. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818617 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Kviman, O., Nilsson, L., and Larsson, M. 2020. [Re] Tensor Monte Carlo: Particle Methods for the GPU Era. ReScience C 6, 2, #5. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818621 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Garg, A. and Kagi, S.S. 2020. [Re] Hamiltonian Neural Networks. ReScience C 6, 2, #3. +
    +
    + + + +
    7. +
  7. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818623 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + + +| BibTeX +
    +     + + + +Ferles, A., Nöu, A., and Valavanis, L. 2020. [Re] Zero-Shot Knowledge Transfer via Adversarial Belief Matching. ReScience C 6, 2, #2. +
    +
    + + + +
    8. +
  8. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818611 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Liu, Y., Xu, J., and Pan, Y. 2020. [Re] When to Trust Your Model: Model-Based Policy Optimization. ReScience C 6, 2, #7. +
    +
    + + + +
    9. +
  9. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818625 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Alacchi, G., Lam, G., and Perreault-Lafleur, C. 2020. [Re] Unsupervised Representation Learning in Atari. ReScience C 6, 2, #1. +
    +
    + + + +
    10. +
  10. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818619 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Gohil, V., Narayanan, S.D., and Jain, A. 2020. [Re] One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. ReScience C 6, 2, #4. +
    +
    + + + +
    11. +
  11. + + + + + Replication + + in NeurIPS 2019 Reproducibility Challenge + + (Python) + + + + + + + + | 10.5281/zenodo.3818605 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Singh, A. and Bay, A. 2020. [Re] Improved Calibration and Predictive Uncertainty for Deep Neural Networks. ReScience C 6, 2, #10. +
    +
    + + + +
+ +

Issue 1 (Ten Years Reproducibility Challenge)

+
  1. + + + + + Replication + + in Computer Science + + (C) + + + + + + + + | 10.5281/zenodo.10275726 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Legrand, A. and Velho, P. 2023. [Re] Velho and Legrand (2009) - Accuracy Study and Improvement of Network Simulation in the SimGrid Framework. ReScience C 6, 1, #20. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computational Neuroscience + + (R) + + + + + + + + | 10.5281/zenodo.5347786 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Eglen, S.J. 2021. [Re] Spatial constraints underlying the retinal mosaics of two types of horizontal cells in cat and macaque. ReScience C 6, 1, #22. +
    +
    + + + +
    3. +
  3. + + + + + Reproduction + + in Earth sciences + + (R) + + + + + + + + | 10.5281/zenodo.4617894 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bond-Lamberty, B. 2021. [Re] Drivers of evapotranspiration from boreal wildfires. ReScience C 6, 1, #21. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Computational Neuroscience + + (C) + + + + + + + + | 10.5281/zenodo.4543356 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Leblois, A. 2021. [Re] Reproduction of the normal and pathological dynamics in the basal ganglia-thalamo-cortical network. ReScience C 6, 1, #19. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Discrete Mathematics + + (C) + + + + + + + + | 10.5281/zenodo.4242972 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Enge, A. 2020. [Re] Volume computation for polytopes: Vingt ans après. ReScience C 6, 1, #17. +
    +
    + + + +
    6. +
  6. + + + + + Reproduction + + in Biology + + (SAS) + + + + + + + + | 10.5281/zenodo.4290512 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Barnett, A. 2020. [Rp] Estimating trends and seasonality in coronary heart disease. ReScience C 6, 1, #18. +
    +
    + + + +
    7. +
  7. + + + + + Reproduction + + in Pattern Recognition + + (Java) + + + + + + + + | 10.5281/zenodo.4091742 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Weinman, J. 2020. [Rp] Reproducing "Typographical Features for Scene Text Recognition". ReScience C 6, 1, #. +
    +
    + + + +
    8. +
  8. + + + + + Reproduction + + in Ecology + + (C, R) + + + + + + + + | 10.5281/zenodo.4081202 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Boettiger, C. 2020. [Rp] Fluctuation domains in adaptive evolution. ReScience C 6, 1, #15. +
    +
    + + + +
    9. +
  9. + + + + + Reproduction + + in Computational Neuroscience + + (Hoc) + + + + + + + + | 10.5281/zenodo.3972130 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Davison, A.P. 2020. [Rp] Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model. ReScience C 6, 1, #14. +
    +
    + + + +
    10. +
  10. + + + + + Reproduction + + in Aquatic Science + + (Pascal) + + + + + + + + | 10.5281/zenodo.3996198 + + + + + | PDF + + + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Silberbauer, M. 2020. Re ReScience challenge: Geographical Trends in the Water Chemistry of Wetlands in the South-Western Cape Province, South Africas. ReScience C 6, 1, #13. +
    +
    + + + +
    11. +
  11. + + + + + Reproduction + + in Astronomy + + (fortran) + + + + + + + + | 10.5281/zenodo.3956058 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Roukema, B.F. 2020. [¬Rp] Reproducibility of ’Poincaré dodecahedral space parameter estimates.’ ReScience C 6, 1, #11. +
    +
    + + + +
    12. +
  12. + + + + + Reproduction + + in Genetics + + (R) + + + + + + + + | 10.5281/zenodo.3959516 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + + +| BibTeX +
    +     + + + +Broman, K.W. 2020. [Rp] Reproducibility report: Identifying essential genes by mutagenesis. ReScience C 6, 1, #12. +
    +
    + + + +
    13. +
  13. + + + + + Reproduction + + in Physics + + (Fortran) + + + + + + + + | 10.5281/zenodo.3922195 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Maggi, S. 2020. [Rp] Reproduction of Step width enhancement in a pulse-driven Josephson junction. ReScience C 6, 1, #10. +
    +
    + + + +
    14. +
  14. + + + + + Reproduction + + in Computational Mechanics + + (C++) + + + + + + + + | 10.5281/zenodo.3901241 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Pantalé, O. 2020. [Rp] Parallelization of an object-oriented FEM dynamics code. ReScience C 6, 1, #8. +
    +
    + + + +
    15. +
  15. + + + + + Reproduction + + in Fault Tolerance + + (C) + + + + + + + + | 10.5281/zenodo.3886739 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Courtès, L. 2020. [Re] Storage Tradeoffs in a Collaborative Backup Service for Mobile Devices. ReScience C 6, 1, #6. +
    +
    + + + +
    16. +
  16. + + + + + Reproduction + + in Fluid dynamics + + (Fortran77) + + + + + + + + | 10.5281/zenodo.3889694 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hinsen, K. 2020. [¬Rp] Stokes drag on conglomerates of spheres. ReScience C 6, 1, #7. +
    +
    + + + +
    17. +
  17. + + + + + Reproduction + + in Computer Science + + (Applesoft Basic) + + + + + + + + | 10.5281/zenodo.3886628 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + + +| BibTeX +
    +     + + + +Rougier, N.P. 2020. [Rp] LOUPE. ReScience C 6, 1, #3. +
    +
    + + + +
    18. +
  18. + + + + + Reproduction + + in Biophysics + + (Python) + + + + + + + + | 10.5281/zenodo.3886447 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hinsen, K. 2020. [Rp] Structural flexibility in proteins - impact of the crystal environment. ReScience C 6, 1, #5. +
    +
    + + + +
    19. +
  19. + + + + + Reproduction + + in Biophysics + + (Mathematica) + + + + + + + + | 10.5281/zenodo.3886412 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Robert, C.H. 2020. [Rp] Reproducibility report: Estimating friction coefficients of mixed globular/chain molecules, such as protein/DNA complexes. [Biophys J 69, 840-848 (1995)]. ReScience C 6, 1, #4. +
    +
    + + + +
    20. +
  20. + + + + + Reproduction + + in Analytical Chemistry + + (FORTRAN77) + + + + + + + + | 10.5281/zenodo.3904595 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Delsuc, M.-A. 2020. [Rp] Gifa V.4: A complete package for NMR data set processing. ReScience C 6, 1, #9. +
    +
    + + + +
    21. +
  21. + + + + + Reproduction + + in Parallel Programming + + (OCaml) + + + + + + + + | 10.5281/zenodo.4041602 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Di Cosmo, R. and Danelutto, M. 2020. [Rp] Reproducing and replicating the OCamlP3l experiment. ReScience C 6, 1, #2. +
    +
    + + + +
    22. +
  22. + + + + + Reproduction + + in Chemical Physics + + (Fortran) + + + + + + + + | 10.5281/zenodo.3630224 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +McBane, G.C. 2020. [Rp] Reproduction of interaction second virial coefficient calculation for H_2–CO interactions [J. Chem. Phys. vol. 112, 4417 (2000)]. ReScience C 6, 1, #1. +
    +
    + + + +
+ +

Volume 5 (2019)

+ +

Issue 3

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.3538217 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Larisch, R. 2019. [Re] Connectivity reflects coding a model of voltage-based STDP with homeostasis. ReScience C 5, 3, #2. +
    +
    + + + +
    2. +
  2. + + + + + Letter + + in Machine Learning + + (c++) + + + + + + + + | 10.5281/zenodo.3528175 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Sukhoy, V. and Stoytchev, A. 2019. Eliminating the Variability of Cross-Validation Results with LIBLINEAR due to Randomization and Parallelization. ReScience C 5, 3, #1. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.3545905 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bock, P. and Alexandre, F. 2019. [Re] The Wisconsin Card Sorting Test: Theoretical analysis and modeling in a neuronal network. ReScience C 5, 3, #3. +
    +
    + + + +
+ +

Issue 2 (ICLR Reproducibility Challenge 2019)

+
  1. + + + + + Editorial + + + + + + + | 10.5281/zenodo.3158244 + + + + + | PDF + + + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Pineau, J., Sinha, K., Fried, G., Ke, R.N., and Larochelle, H. 2019. ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #5. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Machine Learning + + (Python) + + + + + + + + | 10.5281/zenodo.3160540 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Devos, A., Chatel, S., and Grossglauser, M. 2019. [Re] Meta-learning with differentiable closed-form solvers. ReScience C 5, 2, #1. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Machine Learning + + (Python) + + + + + + + + | 10.5281/zenodo.3161734 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Fuente, A.D. la and Aduviri, R. 2019. [Re] Variational Sparse Coding. ReScience C 5, 2, #2. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Machine Learning + + (Python) + + + + + + + + | 10.5281/zenodo.3162890 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bardi, F., von Baussnern, S., and Gjiriti, E. 2019. [Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019. ReScience C 5, 2, #3. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Machine Learning + + (python) + + + + + + + + | 10.5281/zenodo.3162114 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Didolkar, A. 2019. [Re] h-detach: Modifying the LSTM gradient towards better optimization. ReScience C 5, 2, #4. +
    +
    + + + +
+ +

Issue 1

+
  1. + + + + + Replication + + in Ecology + + (Python) + + + + + + + + | 10.5281/zenodo.3234524 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Etherington, T.R. and Lieske, D.J. 2019. [Re] Resampling methods for evaluating classification accuracy of wildlife habitat models. ReScience C 5, 1, #4. +
    +
    + + + +
    2. +
  2. + + + + + Editorial + + + + + + + | 10.5281/zenodo.3069619 + + + + + | PDF + + + + + + + + + + + + + + +| BibTeX +
    +     + + + +Hinsen, K. and Rougier, N.P. 2019. ReScience (R)evolution. ReScience C 5, 1, #3. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.2611252 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Tennøe, S., Hodne, K., Haug, T.M., Weltzien, F.-A., Einevoll, G.T., and Halnes, G. 2019. [Re] Fast-Activating Voltage- and Calcium-Dependent + Potassium (BK) Conductance Promotes Bursting in Pituitary + Cells: A Dynamic Clamp Study. ReScience 5, 1, #2. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Computational Ecology + + (Julia) + + + + + + + + | 10.5281/zenodo.2598793 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Caron, D., Lessard, V., Wu, Q., and Poisot, T. 2019. [Re] Insect natural enemies as regulating factors. ReScience 5, 1, #1. +
    +
    + + + +
+ +

Volume 4 (2018)

+ +

Issue 1

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.1327348 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Hathway, P. and Goodman, D.F.M. 2018. [Re] Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains. ReScience 4, 1, #6. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computational Ecology + + (Julia) + + + + + + + + | 10.5281/zenodo.1402676 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Poisot, T. 2018. [Re] On the coexistence of specialists and generalists. ReScience 4, 1, #7. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.1289889 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Bavard, S. and Théro, H. 2018. [Re] Adaptive properties of differential learning rates for positive and negative outcomes. ReScience 4, 1, #5. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.1246659 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Cazé, R., Stimberg, M., and Girard, B. 2018. [Re] Non-additive coupling enables propagation of + synchronous spiking activity in purely random networks. ReScience 4, 1, #1. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.1244116 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Shimoura, R.O., Kamij, N.L., Pena, R.F.O., et al. 2018. [Re] The cell-type specific cortical microcircuit: relating + structure and activity in a full-scale spiking network + model. ReScience 4, 1, #2. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.1241004 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Senden, M., Schuecker, J., Hahne, J., Diesmann, M., and Goebel, R. 2018. [Re] A neural model of the saccade generator in the + reticular formation. ReScience 4, 1, #3. +
    +
    + + + +
    7. +
  7. + + + + + Replication + + in Computational Biology + + (Python) + + + + + + + + | 10.5281/zenodo.1254629 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Mondeel, T.D.G.A., Ogundipe, V., and Westerhoff, H.V. 2018. [Re] Predicting metabolic biomarkers of human inborn errors + of metabolism. ReScience 4, 1, #4. +
    +
    + + + +
+ +

Volume 3 (2017)

+ +

Issue 1

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.1003214 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Detorakis, G. 2017. [Re] A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors. ReScience 3, 1, #7. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.890901 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Diem, A.K. 2017. [Re] A bidirectional model for communication in the neurovascular unit. ReScience 3, 1, #9. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Evolution + + (R) + + + + + + + + | 10.5281/zenodo.890884 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Stojić, H. 2017. [Re] How learning can guide evolution. ReScience 3, 1, #8. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Game Theory + + (Python) + + + + + + + + | 10.5281/zenodo.847732 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Stollmeier, F. 2017. [Re] A simple rule for the evolution of cooperation on graphs and social networks. ReScience 3, 1, #5. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.854616 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Metzner, C. 2017. [Re] Modeling GABA Alterations in Schizophrenia: A Link Between Impaired Inhibition and Gamma and Beta Auditory Entrainment. ReScience 3, 1, #6. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in Computer Graphics + + (Python) + + + + + + + + | 10.5281/zenodo.802285 + + + + + | PDF + + + + + + | Code + + + + + + + | Data + + + + + + | Review + + + +| BibTeX +
    +     + + + +Rougier, N.P. 2017. [Re] Weighted Voronoi Stippling. ReScience 3, 1, #4. +
    +
    + + + +
    7. +
  7. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.583814 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Rostami, V., Ito, J., Denker, M., and Grün, S. 2017. [Re] Spike Synchronization and Rate Modulation + Differentially Involved in Motor Cortical Function. ReScience 3, 1, #3. +
    +
    + + + +
    8. +
  8. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.495237 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Henriques, R.N., Rokem, A., Garyfallidis, E., St-Jean, S., Peterson, E.T., and Correia, M.M. 2017. [Re] Optimization of a free water elimination + two-compartment model for diffusion tensor imaging. ReScience 3, 1, #2. +
    +
    + + + +
    9. +
  9. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.254145 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Shifman, A. 2017. [Re] Ionic Current Model of a Hypoglossal Motoneuron. ReScience 3, 1, #1. +
    +
    + + + +
+ +

Volume 2 (2016)

+ +

Issue 1

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.200334 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Masson, E.L. and Alexandre, F. 2016. [Re] How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks. ReScience 2, 1, #7. +
    +
    + + + +
    2. +
  2. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.159545 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Vitay, J. 2016. [Re] Robust timing and motor patterns by taming chaos in recurrent neural networks. ReScience 2, 1, #5. +
    +
    + + + +
    3. +
  3. + + + + + Replication + + in Computational Neurosience + + (Python) + + + + + + + + | 10.5281/zenodo.161526 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Maksimov, A., Albada, S.J. van, and Diesmann, M. 2016. [Re] Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model. ReScience 2, 1, #6. +
    +
    + + + +
    4. +
  4. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.61697 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Detorakis, G. 2016. [Re] Multiple dynamical modes of thalamic relay neurons: + rhythmic bursting and intermittent phase-locking. ReScience 2, 1, #4. +
    +
    + + + +
    5. +
  5. + + + + + Replication + + in Computational Ecology + + (R) + + + + + + + + | 10.5281/zenodo.50213 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Petchey, O., Plebani, M., and Pennekamp, F. 2016. [Re] Chaos in a long-term experiment with a plankton community. ReScience 2, 1, #3. +
    +
    + + + +
    6. +
  6. + + + + + Replication + + in Computational Ecology + + (R) + + + + + + + + | 10.5281/zenodo.47146 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Stachelek, J. 2016. [Re] Least-cost modelling on irregular landscape graphs. ReScience 2, 1, #2. +
    +
    + + + +
    7. +
  7. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.45852 + + + + + | PDF + + + + + + | Code + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Viejo, G., Girard, B., and Khamassi, M. 2016. [Re] Speed/accuracy trade-off between the habitual and the + goal-directed process. ReScience 2, 1, #1. +
    +
    + + + +
+ +

Volume 1 (2015)

+ +

Issue 1

+
  1. + + + + + Replication + + in Computational Neuroscience + + (Python) + + + + + + + + | 10.5281/zenodo.27944 + + + + + | PDF + + + + + + | Code + + + + + + + + + + + | Review + + + +| BibTeX +
    +     + + + +Topalidou, M. and Rougier, N.P. 2015. [Re] Interaction between cognitive and motor cortico-basal + ganglia loops during decision making: a computational study. ReScience 1, 1, #1. +
    +
    + + + +
+ +
+ +
+ +
+
+ + + + + + + diff --git a/ten-years-author-guidelines.md b/ten-years-author-guidelines.md new file mode 100644 index 0000000..40ee258 --- /dev/null +++ b/ten-years-author-guidelines.md @@ -0,0 +1,54 @@ +# Author guidelines for reproducibility reports + +The reproducibility reports written by participants in the ten-years challenge are sufficiently different from standard ReScience articles that our standard rules and guidelines make no sense for them. Please use the following guidelines in preparing your submissions! + +## Article + +Please address the following topics to the extent that they make sense for your particular case. + +In addition to the content covered below, we are interested in the insight resulting from +the reproducibility experience in relation to the choice of technology, and in your opinion +on the original source code (clarity, documentation, etc). + +### Historical context + +- Summarize the scientific question that your code was written to explore. +- Describe the computational context: Which hardware was used to run the code? Which software infrastructure? Which constraints existed on software development? Which technical choices (language, libraries, ...) were made? Were reproducibility and/or re-usability important criteria? +- About the original source code: Was it published? Was it archived somewhere? Was there a license for it? + +Please provide only information you are certain about. It's OK to forget technical details after many years. + +### Retrieval of the software + +- Was it easy to find a copy of your source code? +- Was it easy to locate and setup the dependencies? +- Provide a list of all dependencies (libraries but also tools such as compilers). + +### Execution + +Describe what you did in order to run the software today. + +- Did you succeed in running the software in a modern computational environment? Or did you have to search for old versions of tools and libraries? +- Describe the computational environment of the reproduction: hardware, operating system, compiler versions etc. +- Did you have to modify the software in order to make it run today? +- Were the original instructions that came with the software sufficient, or did you have to modify or extend them? +- How close were the results you got to the originally published ones? Include the + replicated data table and figure, as we do in other ReScience articles. + +If you had to make any modifications to the software or to the instructions that were supplied with it, try to describe which competence another researcher would need in order to do the same work. Would a general familiarity with your programming language and environment have been sufficient? + +## Software + +If the licenses applying to the original software allow, please make your old software +available as a repository on GitHub or an equivalent site. In the best case scenario, in +which the old code is publishable, here is the procedure: + +1. Add your old software as a single commit (ideally the initial one) of a new source + repository. +2. Edit the code as necessary to reproduce the results in today's computational environment, + committing the changes in logical units in the process. Include the additional tools + (scripts, makefiles, ...) that you wrote for re-running your software and the additional + instructions. +3. Make sure your repository contains a license. +4. Finaly, submit your repository to [Software Heritage](http://save.softwareheritage.org/) + for archiving. diff --git a/ten-years/index.html b/ten-years/index.html new file mode 100644 index 0000000..78131d7 --- /dev/null +++ b/ten-years/index.html @@ -0,0 +1,267 @@ + + + + + + + + + + + + ReScience C + + + + + + + + + + + +
+ +
+ +
+ ReScience C +
+ + + +
+ +
+ + +
+
+
+ + + +
+

+ +

Ten Years Reproducibility Challenge

+ +

Did you ever try to run old code that you wrote for a scientific article you +published years ago? Did you encounter any problems? Were you successful? +We are curious to hear your story. This is the reason why we are +editing a special issue of ReScience to collect these stories.

+ +

The ten years reproducibility challenge is an invitation for researchers to try +to run the code they’ve created for a scientific publication that was published +more than ten years ago. This code can be anything (statistical analysis, +numerical simulation, data processing, etc.), can be written in any language +and can address any scientific domain. The only mandatory condition to enter +the challenge is to have published a scientific article before 2010, in a +journal or a conference with proceedings, which contains results produced by +code, irrespectively of whether this code was published in some form at the +time or not.

+ +

Note that we do not ask you to write a new version of your old code. We ask you +instead to try to make your old code to run on modern hardware/software +(with minimal modifications) in order to check if you can obtain the exact same +results that were publised at least ten years ago.

+ +

Sounds easy? We have good reasons to think this might be more difficult than you +think. And maybe the first problem you’ll have to solve is to find your own source +code (see the resources section for help).

+ +

Important dates

+ +

The challenge will run for a few months, until ~April 1st, 2020~April 30th, 2020 (because +we’ll need time to review the different submissions). We’ll organize a workshop +in Bordeaux (France) ~on June 22th, 2020~ in autumn (date to be defined) to +present the results. If you intend to participate to the challenge, make sure +to also come to the workshop to hear some scary stories.

+ +

How to enter the challenge ?

+ +

The only mandatory condition to enter the challenge is to have published a +scientific article before January 1st 2010 and this article must have some +computational aspects (i.e. code).

+ +
    +
  • +

    Step 1 You need to declare your interest in the challenge by posting on +this GitHub issue the +article you intend to reproduce (having your article open access would be +great). This does not engage you in any way. We’ll only use this GitHub +thread to gently spam you with a few reminders when we’ll be close to the +deadline (01/04/2020).

    +
    • +
  • +

    Step 2 You have to try to make your old code run on your current +machine, documenting in the process what is necessary to make it work. For +example, you may have to downgrade your system or some libraries, to modify +your original code because some library is nowhere to be found, to reinstall a +specific compiler or interpreter, etc. In the end, there may be large number +of different situations: you are unable to run or compile the code, you are +able to run the code but it does not give you the expected results (or no +result at all), the program crashed regularly (before getting results), you +do not remember how to run your program, etc.

    +
    • +
  • +

    Step 3 You have to write a reproducibility report for ReScience (any +number of pages) and submit it. You’ll have to indicate that this submission +is for the ten years special issue. Since these reproducibility reports +are rather different from regular ReScience articles, please check the +author guidelines +that we have prepared specifically for this special issue (and be aware that +they might still evolve a bit).

    +
    • +
  • +

    Step 4 Interact with reviewers during the open peer review and have your +article published open access (no APC, ReScience is free to read and free to +publish).

    +
    • +
  • +

    Step 5 Come to visit us in Bordeaux and attend the workshop in June (date +not yet settled) where we’ll introduce the results of the challenge. We’ll +also have a bunch of great talks on reproducibility and replicability.

    +
    • +
+ +

Frequently Asked Questions

+ +

Is there a prize for the challenge? Yes, you will get all our +consideration. More seriously, there is nothing to gain but insight on +the reasons why a code becomes non reproducible. We can also send you a print of +the cool poster above (A2 format).

+ +

Can I run the code from someone else? No, because we want original authors +to re-run their own code. However, if you’re interested in trying to run code +from someone else, you can submit a “reproducibility report” that will be +published in a regular issue of ReScience (if accepted after open peer-review).

+ +

I cannot find my source code, can I enter the challenge? It mostly depends +if you have a good story to explain why you do not have your code anymore. +Writing an article just to say you failed because you did not find the code +does not sound very exciting. But still, we would like to hear from you. Be +assured you’re certainly not the only one in that situation.

+ +

My original code has been used, converted, modified, upgraded and I’m sure it +is reproducible That’s good. But what about the original version of the code, +the one you wrote for your article ? This is this code we want to put to the +test.

+ +

Is it ok to submit an article stating I cannot reproduce my results? +Yes. We actually expect this case to correspond to the majority of +situations. There are many possible reasons and we’re interested in knowing +the exact reasons that prevented you from getting your original results.

+ +

Is it ok to submit a one page article stating everything ran fine? +Yes. But you’ll need to give us some details on how you did it (what language, +what OS, how are you sure you get the same results, etc.). This will serve for +a study on what are the best languages, libraries, and tools for reproducibility.

+ +

Resources

+ +
    +
  • +

    The Wayback Machine is a digital archive of the World +Wide Web and other information on the Internet. It was launched in 2001 by +the Internet Archive, a nonprofit organization based in San Francisco, +California, United States.

    +
    • +
  • +

    Software Heritage’s ambition is to collect, +preserve, and share all software that is publicly available in source code +form. On this foundation, a wealth of applications can be built, ranging from +cultural heritage to industry and research.

    +
    • +
  • +

    Guix supports transactional upgrades and roll-backs, +unprivileged package management, and more. When used as a standalone +distribution, Guix supports declarative system configuration for transparent +and reproducible operating systems.

    +
    • +
  • +

    Debian is a free operating system (OS) +with reproducible build +capacity, archive of the packages for the past +releases (since 1998) and +daily snapshots since 2005, making it +feasible to find old versions of software of interest and +debootstrap old environments.

    +
    • +
  • +

    The National Museum of Computing is home to the +world’s largest collection of working historic computers.

    +
    • +
  • +

    3.5” Floppy Disk +readers, +Compat Disc readers +(on Amazon). Just in case you source code is only available on one of this +archaic supports…

    +
    • +
+ +
+ +
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Overview of the submission process

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The ReScience C editorial board unites scientists who are committed to the open +source community. Each editorial board member is specialised in a specific +domain of science and is proficient in several programming languages and/or +environments. Our aim is to provide all authors with an efficient, constructive +and public editorial process.

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Submitted entries are first considered by a member of the editorial board, who +may decide to reject the submission (mainly because it has already been +replicated and is publicly available), or assign it to two reviewers for +further review and tests. The reviewers evaluate the code and the accompanying +material in continuous interaction with the authors through the PR discussion +section. If both reviewers managed to run the code and obtain the same results +as the ones advertised in the accompanying material, and if they consider that +these results are a replication of the original work, the submission is +accepted. If any of the two reviewers cannot reproduce the results before the +deadline, the submission is rejected and authors are encouraged to resubmit an +improved version later.

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How to submit?

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  • Upload your code to a public repository +(e.g. GitHub)
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  • Upload your data (if any) to a public repository +(e.g. Zenodo)
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  • Write the corresponding paper using the proposed +LaTeX template +or your own template
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  • Fill metadata associated with your submission using the +provided template
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  • Submit your paper
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  • Answer reviewers comments and modify your code and paper accordingly
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  • Once accepted, you will need to: +
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    • complete the metadata in collaboration with the editor
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    • upload your code +to Zenodo in order to get a DOI.
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Criteria for Publication

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To be considered for publication in ReScience C, any given submission must +satisfy the following criteria:

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  • Rigorous methodology
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  • Original source code
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  • Substantial evidence for replication of the original results or +explanations why original results cannot be replicated
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Furthermore, you cannot submit the replication of your own research, nor the +research of your close collaborators. We believe such restrictions will favor +the cross-fertilization of research and the spread of knowledge.

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ReScience C accepts negative results as well, meaning here a failure to +replicate the original results. The authors of the failed replication are +expected to document their claim of failure, and to have attempted to contact +the authors of the original article.

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Article Scope

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The accompanying article should help the reader ascertain if the replication was +successful and as such, the main focus should be on the replicated results and +on any obstacles encountered during the replication.

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In many cases it can be useful to include high-level summaries of the original +model or of your source code. Your goal should be to make the article +sufficiently self-contained, but not to repeat all aspects of the original +article or your documentation. Which amount of detail is sufficient may vary +from case to case and is ultimately up to the reviewers to judge. If a reader +has to be familiar with the original article in order to understand your +explanations, consider that some readers may be unable to access it if it is +behind a paywall.

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Open Access

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ReScience C applies the Creative Commons Attribution (CC BY) license to all +works it publishes. Under the CC BY license, authors retain ownership of the +copyright for their article, but authors allow anyone to download, reuse, +reprint, modify, distribute, and/or copy articles in ReScience C journal, so +long as the original authors and source are cited. No permission is required +from the authors or the publishers.

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