quaquel/EMAworkbench

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

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 Python sandbox for decision making in dynamics

Probabilistic modelling and uncertainty quantification library

RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.

Emulate simulations easily

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

Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.

The core Dakota project