Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
-
Updated
Jul 9, 2024 - Python
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
A Library for Uncertainty Quantification.
Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.
Lightweight, useful implementation of conformal prediction on real data.
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language 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.
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
Chaospy - Toolbox for performing uncertainty quantification.
Conformal classifiers, regressors and predictive systems
A Python library for amortized Bayesian workflows using generative neural networks.
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.
Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.
Open-source framework for uncertainty and deep learning models in PyTorch 🌱
Uncertainty treatment library
Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
Add a description, image, and links to the uncertainty-quantification topic page so that developers can more easily learn about it.
To associate your repository with the uncertainty-quantification topic, visit your repo's landing page and select "manage topics."