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Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
The Python ensemble sampling toolkit for affine-invariant MCMC
Bayesian inference with probabilistic programming.
Owl - OCaml Scientific and Engineering Computing @ http://ocaml.xyz
Boltzmann Machines in TensorFlow with examples
Bayesian Data Analysis demos for Python
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
Bayesian Data Analysis demos for R
High-performance Bayesian Data Analysis on the GPU in Clojure
bayesplot R package for plotting Bayesian models
Collection of probabilistic models and inference algorithms
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
shinystan R package and ShinyStan GUI
Bayesian Evolutionary Analysis by Sampling Trees
DGMs for NLP paper list
Manifold Markov chain Monte Carlo methods in Python
Fast & scalable MCMC for all your exoplanet needs!
Bayesian Evolutionary Analysis Sampling Trees
GPstuff - Gaussian process models for Bayesian analysis
PhyML -- Phylogenetic estimation using (Maximum) Likelihood
A repository to keep track of all the code that I end up writing for my blog posts.
Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!
The base NIMBLE package for R
Types and utility functions for summarizing Markov chain Monte Carlo simulations
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
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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