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487 public repositories
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Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
Updated
Jul 30, 2021
Python
Bayesian inference with probabilistic programming.
Updated
Jul 18, 2021
Julia
The Python ensemble sampling toolkit for affine-invariant MCMC
Updated
Jul 21, 2021
Python
Updated
Jul 8, 2021
OCaml
Bayesian Data Analysis demos for Python
Updated
Jul 19, 2021
Jupyter Notebook
RStan, the R interface to Stan
Boltzmann Machines in TensorFlow with examples
Updated
Aug 1, 2020
Jupyter Notebook
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
Jul 27, 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
A repository to keep track of all the code that I end up writing for my blog posts.
Updated
Oct 1, 2020
Jupyter Notebook
shinystan R package and ShinyStan GUI
Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.
Updated
Jun 25, 2021
Julia
Manifold Markov chain Monte Carlo methods in Python
Updated
Apr 6, 2021
Python
Bayesian Evolutionary Analysis by Sampling Trees
Updated
Jul 30, 2021
Java
Types and utility functions for summarizing Markov chain Monte Carlo simulations
Updated
Jul 30, 2021
Julia
Fast & scalable MCMC for all your exoplanet needs!
Updated
Jul 28, 2021
Python
Bayesian Evolutionary Analysis Sampling Trees
Updated
Jul 28, 2021
Java
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
Updated
Jul 15, 2021
Julia
GPstuff - Gaussian process models for Bayesian analysis
Updated
Aug 5, 2020
MATLAB
Implementation of Markov Chain Monte Carlo in Python from scratch
Updated
Aug 20, 2020
Jupyter Notebook
ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.
Updated
Jul 12, 2021
Fortran
PhyML -- Phylogenetic estimation using (Maximum) Likelihood
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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