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

Public facing deeplift repo

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

Official development repository for SUNDIALS - a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. Pull requests are welcome for bug fixes and minor changes.

Chaospy - Toolbox for performing uncertainty quantification.

Tensorflow tutorial for various Deep Neural Network visualization techniques

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.

Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner

The Biorefinery Simulation and Techno-Economic Analysis Modules; Life Cycle Assessment; Chemical Process Simulation Under Uncertainty

Frequency-domain photonic simulation and inverse design optimization for linear and nonlinear devices

tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis

Advanced Multilanguage Interface to CVODES and IDAS

MADS: Model Analysis & Decision Support

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

ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis

Multiphysics Finite Element package built on libMesh

OpenCossan is an open and free toolbox for uncertainty quantification and management.

Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia

priorsense: an R package for prior diagnostics and sensitivity