Bayesian Modeling and Probabilistic Programming in Python
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Bayesian inference with probabilistic programming.
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
The Python ensemble sampling toolkit for affine-invariant MCMC
Owl - OCaml Scientific Computing @ https://ocaml.xyz
RStan, the R interface to Stan
Bayesian Data Analysis demos for Python
Boltzmann Machines in TensorFlow with examples
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
bayesplot R package for plotting Bayesian models
DGMs for NLP. A roadmap.
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.
High-performance Bayesian Data Analysis on the GPU in Clojure
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
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