Markov Chain Monte Carlo Python Packages

netket

Machine learning algorithms for many-body quantum systems

gpflow

Gaussian processes in TensorFlow

curvesimulator

CurveSimulator is a reliable n-Body Python package for fast and flexible Orbital Parameter Determination (MCMC). It can also generate highly configurable videos for teaching, public outreach, and scientific insight.

bisip

BISIP | Bayesian inversion of spectral induced polarization laboratory data

pymcmcstat

Python implementation of MATLAB toolbox "mcmcstat"

dnest4

Diffusive Nested Sampling

mici

Manifold Markov chain Monte Carlo methods in Python

openmmtools

A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.

lilit

Likelihood for LiteBIRD

littlemcmc

A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.

bayestorch

Lightweight Bayesian deep learning library for fast prototyping based on PyTorch

occuspytial

A package for fast bayesian analysis of single season spatial occupancy models.

mcmc-samplers

A Python package for MCMC sampling.

mcmcallotter

This is a python package based on the source code for "An MCMC Based Course to Teaching Assistant Allocation", S. Kumar, S. Moothedath, P. Chaporkar, M. Belur, Proceedings of the Fifth International Conference on Network, Communication and Computing (2016). ACM.

ls-mcmc

A light-weight library for large-scale Markov Chain Monte Carlo sampling

gpflow-old

Gaussian processes in TensorFlow

monte-library

Monte is a set of Monte Carlo methods in Python. The package is written to be flexible, clear to understand and encompass variety of Monte Carlo methods.

hmclab

A numerical laboratory for Bayesian Seismology