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

getdist

MCMC sample analysis, kernel densities, plotting, and GUI

bnlearn

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

zeus-mcmc

⚡️ zeus: Lightning Fast MCMC ⚡️

dppy

Python toolbox for sampling Determinantal Point Processes

blackjax-nightly

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

torchebm

🍓 Build and train energy-based and diffusion models in PyTorch ⚡.

pyapr

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

pocomc

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

copulax

Copula, multivariate and univariate distribution fitting using JAX in python.

ontosample

OntoSample is a python package that offers classic sampling techniques for OWL ontologies/knowledge bases. Furthermore, we have tailored the classic sampling techniques to the setting of concept learning making use of learning problem.

sgmcmcjax

SGMCMC samplers in JAX

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.

selene-sdk

a framework for training sequence-level deep learning networks

py-bnlearn

bnlearn is a Python package for Causal Discovery by learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

bajes

Bayesian Jenaer software

outrank

OutRank: Feature ranking for massive sparse data sets.

jaxampler

An open-source JAX-based statistical sampling toolkit 🧪

active-sample

An active learning sampler

mcmc-samplers

A Python package for MCMC sampling.

fldr

Fast Loaded Dice Roller

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.

sklearn-contrib-bde

Bayesian Deep Ensembles with MILE (JAX), scikit-learn style.