Sampling Methods Python Packages

blackjax

BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.

pydoe3

Design of experiments for Python

bnlearn

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

getdist

MCMC sample analysis, kernel densities, plotting, and GUI

zeus-mcmc

⚡️ zeus: Lightning Fast MCMC ⚡️

blackjax-nightly

BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.

dppy

Python toolbox for sampling Determinantal Point Processes

sgmcmcjax

SGMCMC samplers in JAX

copulax

JAX-based copula modelling

pyapr

Content-adaptive storage and processing of large volumetric microscopy data using the Adaptive Particle Representation (APR)

globaloptimizationhrla

A package to solve global optimization problems in small dimensions. The method is based on sampling algorithms, and specifically implements the high-resolution Langevin algorithm.

pocomc

Preconditioned Monte Carlo

torchebm

Components and algorithms for energy-based models

ontosample

Ontosample is a package that offers different sampling techniques for OWL ontologies.

bajes

Bayesian Jenaer software

selene-sdk

a framework for training sequence-level deep learning networks

active-sample

Implementation of active learning sampler

outrank

OutRank: Feature ranking for massive sparse data sets.

jaxampler

An open-source JAX-based statistical sampling toolkit 🧪

fldr

Fast Loaded Dice Roller

mcmc-samplers

A Python package for MCMC sampling.

sklearn-contrib-bde

Bayesian Deep Ensembles via MILE: easy to use, scikit-learn compatible and fast (JAX powered)

sampling-utils

Python tools to sample randomly with dont pick closest `n` elements constraints. Also contains a batch generator for the same to sample with replacement and with repeats if necessary.

cronus-mcmc

cronus: MCMC + MPI MADE EASY