Structured state space sequence models
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Jul 17, 2024 - Jupyter Notebook
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state-space-models
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Code Repository for Liquid Time-Constant Networks (LTCs)
deep-learning time-series recurrent-neural-networks state-space-models sequence-modeling liquid-neural-networks
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Jun 3, 2024 - Python
A Python package for probabilistic state space modeling with JAX
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Sep 1, 2026 - Python
Liquid Structural State-Space Models
deep-learning time-series recurrent-neural-networks neural-networks state-space-models sequence-modeling liquid-neural-networks
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Feb 1, 2024 - Python
Reading list for research topics in state-space models
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May 18, 2026
DeepTab is a Python package that simplifies tabular deep learning by providing a suite of models for regression, classification, and distributional regression tasks. It includes models such as Mambular, TabM, FT-Transformer, TabulaRNN, TabTransformer, and tabular ResNets.
node regression classification rnn resnet deeplearning preprocessing ssm mamba saint state-space-models ple distributional-regression tabtransformer ft-transformer tabular-deep-learning tabm
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Sep 13, 2026 - Python
StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.
statistics time-series julia-language econometrics forecasting kalman-filter time-series-analysis exponential-smoothing state-space-models sarima unobserved-components
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Aug 24, 2026 - Julia
Official code for Echo-Memory: a controlled study of memory in action-conditioned video world models (Context, Compression, Spatial, State-Space).
computer-vision memory pytorch wan spatial-memory state-space-models video-generation image-to-video world-models diffusion-models generative-ai action-conditioned video-world-models
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Aug 16, 2026 - Python
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
machine-learning signal-processing gaussian-processes state-space-models jax approximate-bayesian-inference sparse-gps markov-gps
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Dec 22, 2023 - Python
R code for Time Series Analysis and Its Applications, Ed 4
data-science r data-analysis missing-data time-domain frequency-domain kalman-filter em-algorithm time-series-analysis state-space-models astsa
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Aug 20, 2025
Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
machine-learning bayesian-methods probabilistic-programming probabilistic-graphical-models factor-graph state-space-models
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May 3, 2023 - Julia
[CVPR'24 Spotlight] The official implementation of "State Space Models for Event Cameras"
machine-learning deep-neural-networks deep-learning spotlight machine-learning-algorithms transformers recurrent-neural-networks transformer rnn neuromorphic ssm ssms rnns rnn-pytorch state-space-model state-space-models state-space-representation event-cameras event-camera vision-transformer
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Sep 28, 2024 - Python
R package to accompany Time Series Analysis and Its Applications: With R Examples -and- Time Series: A Data Analysis Approach Using R
package data-science r data-analysis missing-data kalman-filter em-algorithm dna-sequences time-series-analysis state-space-models astsa
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Sep 8, 2026 - R
[ACM MM'24 Oral] RainMamba: Enhanced Locality Learning with State Space Models for Video Deraining
video-processing mamba image-restoration restoration state-space-models low-level-vision video-enhancement deraining video-restoration video-deraining mamba-state-space-models vision-mamba video-mamba acmmm2024
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Sep 22, 2025 - Python
Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
machine-learning signal-processing gaussian-processes state-space-models kalman-smoother approximate-bayesian-inference
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Jul 6, 2023 - Jupyter Notebook
The official codebase of the paper "Chemical language modeling with structured state space sequence models"
deep-learning chemistry cheminformatics s4 state-space-models smiles-strings de-novo-drug-design chemical-language-models
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Aug 1, 2024 - HTML
Package implementing common state-space routines.
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Jul 27, 2026 - Julia
Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
reinforcement-learning deep-reinforcement-learning s6 ssm mamba s5 s4 deep-rl model-based-rl state-space-models model-based-reinforcement-learning dreamer world-models parallel-scan iclr2024 parallel-scanning
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Jun 4, 2024 - Python
An interpretable foundation model of the patient clinical timeline: event forecasting, calibrated time-to-event alerts, and concept-level interpretability, benchmarked head-to-head against tuned GBMs, tabular foundation models, and survival baselines on MIMIC-IV, eICU, and GEMINI via the MEDS standard.
machine-learning transformers pytorch healthcare survival-analysis ehr mamba electronic-health-records medical-informatics time-to-event interpretability state-space-models meds eicu clinical-ai mimic-iv foundation-models concept-bottleneck
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Sep 11, 2026 - Python
Multivariate Autoregressive State-Space Modeling with R
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Sep 9, 2025 - R
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