Mcmc Python Packages

pymc

Bayesian Modeling and Probabilistic Programming in Python

numpyro

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

emcee

The Python ensemble sampling toolkit for affine-invariant MCMC

pymc3

Bayesian Modeling and Probabilistic Programming in Python

getdist

MCMC sample analysis, kernel densities, plotting, and GUI

autofit

PyAutoFit: Classy Probabilistic Programming

anesthetic

Nested Sampling post-processing and plotting

zeus-mcmc

⚡️ zeus: Lightning Fast MCMC ⚡️

aemcmc-nightly

Miscellaneous MCMC samplers written in Aesara

flowmc

Normalizing-flow enhanced sampling package for probabilistic inference in JAX

bsts-causalimpact

Bayesian CausalImpact for Python — R-compatible Gibbs sampler in Rust (PyO3), 30x faster, no TensorFlow

stochopy

Python library for stochastic numerical optimization

vip-hci

VIP is a python package/library for angular, reference star and spectral differential imaging for exoplanet/disk detection through high-contrast imaging.

emodel-generalisation

Generalisation of electrical models of neurons with MCMC

paramonte

ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.

gerrychain

Use MCMC to analyze districting plans and gerrymanders

inference-tools

Python tools for Bayesian data analysis

bask

A fully Bayesian implementation of sequential model-based optimization

dedekind

Dedekind is a high-performance, differentiable programming language for scientific computing and machine learning. It features compile-time physical units, automatic differentiation, built-in solvers, and GPU/TPU acceleration.

mc3

Python MCMC Sampler

autoemulate

Emulate simulations easily

pocomc

pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation

aehmc

HMC samplers in Aesara

pymhss

No description available