Here are
454 public repositories
matching this topic...
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
Updated
Apr 12, 2021
Python
Bayesian inference with probabilistic programming.
Updated
Apr 12, 2021
Julia
The Python ensemble sampling toolkit for affine-invariant MCMC
Updated
Feb 18, 2021
Python
Updated
Apr 10, 2021
OCaml
Bayesian Data Analysis demos for Python
Updated
Sep 8, 2020
Jupyter Notebook
Boltzmann Machines in TensorFlow with examples
Updated
Aug 1, 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
Apr 13, 2021
Julia
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
Updated
Dec 20, 2017
Python
Collection of probabilistic models and inference algorithms
Updated
Apr 3, 2020
Python
shinystan R package and ShinyStan GUI
Manifold Markov chain Monte Carlo methods in Python
Updated
Apr 6, 2021
Python
Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.
Updated
Mar 22, 2021
Julia
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
Types and utility functions for summarizing Markov chain Monte Carlo simulations
Updated
Apr 13, 2021
Julia
Fast & scalable MCMC for all your exoplanet needs!
Updated
Apr 6, 2021
Python
Bayesian Evolutionary Analysis Sampling Trees
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
Updated
Apr 12, 2021
Julia
GPstuff - Gaussian process models for Bayesian analysis
Updated
Aug 5, 2020
MATLAB
PhyML -- Phylogenetic estimation using (Maximum) Likelihood
Implementation of Markov Chain Monte Carlo in Python from scratch
Updated
Aug 20, 2020
Jupyter Notebook
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
Updated
Mar 26, 2021
Python
Improve this page
Add a description, image, and links to the
mcmc
topic page so that developers can more easily learn about it.
Curate this topic
Add this topic to your repo
To associate your repository with the
mcmc
topic, visit your repo's landing page and select "manage topics."
Learn more
You can’t perform that action at this time.
You signed in with another tab or window. Reload to refresh your session.
You signed out in another tab or window. Reload to refresh your session.
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