JuliaUQ/UncertaintyQuantification.jl

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

Stochastic Optimization, Learning, Uncertainty and Sampling

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

Uncertainty Quantification using Polynomial Chaos Expansion (UQPCE) is an open-source, python-based research code for use in parametric, non-deterministic computational studies. UQPCE utilizes a non-intrusive polynomial chaos expansion surrogate modeling technique to efficiently estimate uncertainties for computational analyses.

Probabilistic modelling and uncertainty quantification library

Derivative-free parameter calibration and uncertainty quantification for expensive models using ensemble Kalman methods

Uncertainty quantification with PyTorch

Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration.