Uncertainty Quantification Python Packages

salib

Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.

emukit

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

crepes

Python package for conformal prediction

uncertainty-toolbox

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

xdem

Analysis of digital elevation models and elevation point clouds

deephyper

DeepHyper: A Python Package for Massively Parallel Hyperparameter Optimization in Machine Learning

puncc

👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.

uqlm

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

pygpc

A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method

med3pa

Python Open-source package for ensuring robust and reliable ML models deployments

uqpy

UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.

mogp-emulator

Package for fitting Gaussian Process Emulators to multiple output computer simulation results.

monte-carlo-sensitivity

Monte Carlo Sensitivity Analysis

torch-uncertainty

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

easyvvuq

Python 3 framework to facilitate verification, validation and uncertainty quantification (VVUQ) for a wide variety of simulations.

monaco

Quantify uncertainty and sensitivities in your computer models with an industry-grade Monte Carlo library.

autoemulate

Emulate simulations easily

ecov003-l2t-stars

ECOSTRESS Collection 3 Level 2 Spatial Timeseries for Automated high-Resolution multi-Sensor (STARS) Data Fusion System

bayesian-torch

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

nonconform

Conformal Anomaly Detection & Change-Point Detection

aimz

Scalable probabilistic impact modeling

apdtflow

APDTFlow: A modular forecasting framework for time series data

torchcp

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

tablespoon

🥄✨Time-series Benchmark methods that are Simple and Probabilistic