MUQ: The MIT Uncertainty Quantification Library

Welcome to MUQ (pronounced “muck”), a modular software framework for defining and solving forward and inverse uncertainty quantification problems.

Uncertainty quantification (UQ) is important in many different applications. MUQ aims to make advanced probabilistic UQ tools easy to use in either c++ or python, and enable cutting-edge method development through its modular structure.

MUQ has a variety of capabilities, including:

• Various Markov chain Monte Carlo methods
• Graphical modeling with a mix of statistical and physical components
• Gaussian processes
• Karhunen Loève expansions
• Transport maps
• Nonlinear Optimization
• Generalized Polynomial Chaos Expansions

This version of MUQ was put forward to the Journal of Open Source Software for review in 2021. The development of MUQ continues at https://bitbucket.org/mituq/muq2.