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The Wayback Machine - https://web.archive.org/web/20210102182955/https://github.com/topics/mcmc
Here are
431 public repositories
matching this topic...
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
Updated
Jan 2, 2021
Python
The Python ensemble sampling toolkit for affine-invariant MCMC
Updated
Dec 29, 2020
Python
Bayesian inference with probabilistic programming.
Updated
Dec 28, 2020
Julia
Updated
Dec 27, 2020
OCaml
Boltzmann Machines in TensorFlow with examples
Updated
Aug 1, 2020
Jupyter Notebook
Bayesian Data Analysis demos for Python
Updated
Sep 8, 2020
Jupyter Notebook
RStan, the R interface to Stan
Bitmap generation from a single example with convolutions and MCMC
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
Updated
Oct 26, 2020
Jupyter Notebook
Bayesian Data Analysis demos for R
High-performance Bayesian Data Analysis on the GPU in Clojure
Updated
Sep 10, 2020
Clojure
bayesplot R package for plotting Bayesian models
Julia version of selected functions in the R package `rethinking`. Used in the StatisticalRethinkingStan and StatisticalRethinkingTuring projects.
Updated
Jan 2, 2021
Julia
Collection of probabilistic models and inference algorithms
Updated
Apr 3, 2020
Python
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
Updated
Dec 20, 2017
Python
shinystan R package and ShinyStan GUI
Stan.jl illustrates the usage of the new 'single method' packages, e.g. StanSample, StanOptimize, etc.
Updated
Dec 26, 2020
Julia
Manifold Markov chain Monte Carlo methods in Python
Updated
Dec 17, 2020
Python
Bayesian Evolutionary Analysis by Sampling Trees
A repository to keep track of all the code that I end up writing for my blog posts.
Updated
Oct 1, 2020
Jupyter Notebook
Fast & scalable MCMC for all your exoplanet needs!
Updated
Dec 31, 2020
Python
Bayesian Evolutionary Analysis Sampling Trees
Updated
Dec 29, 2020
Java
GPstuff - Gaussian process models for Bayesian analysis
Updated
Aug 5, 2020
MATLAB
Types and utility functions for summarizing Markov chain Monte Carlo simulations
Updated
Dec 25, 2020
Julia
PhyML -- Phylogenetic estimation using (Maximum) Likelihood
Graphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
Updated
Nov 14, 2020
Python
Bayesian Statistics I at Stockholm University
Updated
Dec 16, 2020
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Hi @JavierAntoran @stratisMarkou,
First of all, thanks for making all of this code available - it's been great to look through!
Im currently spending some time trying to work through the Weight Uncertainty in Neural Networks in order to implement Bayes-by-Backprop. I was struggling to understand the difference between your implementation of `Bayes-by-Bac