Alternatives and similar repositories for MCMC:

Users that are interested in MCMC are comparing it to the libraries listed below

• Joseph94m / MCMC
  Implementation of Markov Chain Monte Carlo in Python from scratch
  ☆210Updated 4 years ago
• dfm / george
  Fast and flexible Gaussian Process regression in Python
  ☆456Updated last week
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆241Updated 4 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆227Updated 2 months ago
• dilinwang820 / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆397Updated last year
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆268Updated 5 years ago
• mfouesneau / NUTS
  python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011
  ☆127Updated 4 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆244Updated 3 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆214Updated 6 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆186Updated 4 years ago
• mcleonard / sampyl
  MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice
  ☆336Updated 2 years ago
• leowyy / mcmc-importance-sampling
  Markov Chain Monte Carlo (MCMC) and importance sampling in the context of Bayesian linear regression
  ☆11Updated 7 years ago
• PredictiveScienceLab / uq-course
  Introduction to Uncertainty Quantification
  ☆245Updated 3 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆233Updated 3 years ago
• paraschopra / bayesian-neural-network-mnist
  Bayesian neural network using Pyro and PyTorch on MNIST dataset
  ☆311Updated 6 years ago
• axelbrando / Mixture-Density-Networks-for-distribution-and-uncertainty-estimation
  A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
  ☆349Updated 7 years ago
• thuijskens / bayesian-optimization
  Python code for bayesian optimization using Gaussian processes
  ☆311Updated 8 years ago
• Gabriel-p / pythonMCMC
  A list of Python-based MCMC & ABC packages
  ☆123Updated 9 months ago
• jamesrobertlloyd / gp-structure-search
  ☆232Updated 7 years ago
• ColCarroll / minimc
  Just a little MCMC
  ☆223Updated 9 months ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆203Updated 4 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆149Updated 6 years ago
• pmelchior / pygmmis
  Gaussian mixture model for incomplete (missing or truncated) and noisy data
  ☆99Updated 2 years ago
• simetenn / uncertainpy
  Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
  ☆228Updated 2 years ago
• tensorchiefs / dl_book
  legend
  ☆199Updated last year
• minaskar / zeus
  ⚡️ zeus: Lightning Fast MCMC ⚡️
  ☆232Updated last year
• fonnesbeck / gp_regression
  A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)
  ☆165Updated 3 years ago
• NicolasDurrande / Gaussian-Process-Regression-handout
  ☆38Updated 8 years ago
• msmbuilder / vde
  Variational Autoencoder for Dimensionality Reduction of Time-Series
  ☆186Updated 2 years ago
• Harry24k / bayesian-neural-network-pytorch
  PyTorch implementation of bayesian neural network [torchbnn]
  ☆521Updated 8 months ago