Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
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Updated
Mar 5, 2025 - Python
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.
Lightweight, useful implementation of conformal prediction on real data.
A Library for Uncertainty Quantification.
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
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
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
Python package for conformal prediction
Chaospy - Toolbox for performing uncertainty quantification.
A Python toolbox for conformal prediction research on deep learning models, using PyTorch.
Open-source framework for uncertainty and deep learning models in PyTorch 🌱
👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
DeepHyper: A Python Package for Massively Parallel Hyperparameter Optimization in Machine Learning
Probabilistic modelling and uncertainty quantification library
Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.
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