Popular GitHub Repositories for Quantification

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

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

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

Python package for conformal prediction

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.

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification (https://deepliif.org) [Nature Machine Intelligence'22, CVPR'22, MICCAI'23, Histopathology'23, MICCAI'24]

Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.

Conformal prediction for time-series applications.

Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).

Repo of "Quantification of Large Language Model Distillation"

Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Fast uncertainty quantification for scientific machine learning (SciML) and differential equations