Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Natural Gradient Boosting for Probabilistic Prediction
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
[JMLR 2026] "UQLM: A Python Package for Uncertainty Quantification in Large Language Models"
Lightweight, useful implementation of conformal prediction on real data.
A Library for Uncertainty Quantification.
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
Curated list of open source tooling for data-centric AI on unstructured data.
An extension of XGBoost to probabilistic modelling
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.
[TMECH'2024] PALoc: Advancing SLAM Benchmarking with Prior-Assisted 6-DoF Trajectory Generation and Uncertainty Estimation
An extension of LightGBM to probabilistic modelling
[ICRA@40] MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
[CVPR 2024 Award Candidate] Producing and Leveraging Online Map Uncertainty in Trajectory Prediction
Quantile Regression Forests compatible with scikit-learn.
[ICCV 2021 Oral] Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
CVPR 2020 - On the uncertainty of self-supervised monocular depth estimation
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