Popular GitHub Repositories for Uncertainty Quantification

Time series forecasting with PyTorch

Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"

Natural Gradient Boosting for Probabilistic Prediction

Lightweight, useful implementation of conformal prediction on real data.

UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

Pool-based active learning in Python

Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models

Curated list of open source tooling for data-centric AI on unstructured data.

Bounding Box Regression with Uncertainty for Accurate Object Detection (CVPR'19)

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving (ICCV, 2019)

An extension of XGBoost to probabilistic modelling

Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations

Python package for conformal prediction

Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"

A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.

Open-source framework for uncertainty and deep learning models in PyTorch :seedling:

A Python toolbox for conformal prediction research on deep learning models, using PyTorch.

A curated list of trustworthy deep learning papers. Daily updating...

A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)