SALib/SALib

SMT: The Surrogate Modeling Toolbox

Exploratory analysis of Bayesian models with Python

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

Causal Inference in Python

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

A Python implementation of global optimization with gaussian processes.

OpenMDAO repository.