78 Open source projects that are alternatives of or similar to Turingmodels.jl

A C++ library of Markov Chain Monte Carlo (MCMC) methods

Multi-core BUGS for fast Bayesian inference of large hierarchical models

Bitmap generation from a single example with convolutions and MCMC

CmdStanR: the R interface to CmdStan

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Bayesian Data Analysis demos for Python

BAS R package https://merliseclyde.github.io/BAS/

The Python ensemble sampling toolkit for affine-invariant MCMC

Markov chain Monte Carlo solver for lattice spin systems implemented by Julialang

bayesplot R package for plotting Bayesian models

Full Bayesian Inference for Hidden Markov Models

DynamicHMC versions of StatisticalRethinking models

Owl - OCaml Scientific and Engineering Computing @ http://ocaml.xyz

Start with the Chempy tutorial

Bayesian inference with probabilistic programming.

Material for a workshop on Bayesian stats with R

RStan, the R interface to Stan

CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations

A Bayesian Analysis Toolkit in Julia

Nested Sampling post-processing and plotting

Bayesian Data Analysis demos for R

machine learning

CmdStan.jl v6 provides an alternative, older Julia wrapper to Stan's `cmdstan` executable.

Blang's software development kit

Automatic Reparameterisation of Probabilistic Programs

library of C++ functions that support applications of Stan in Pharmacometrics

An R package to manipulate MCMC samples

Make a sweet giant triangle confusogram (GTC) plot

A multi-planet Radial Velocity and Transit modelling software

Use MCMC to analyze districting plans and gerrymanders

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

PhyML -- Phylogenetic estimation using (Maximum) Likelihood

ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.

Application of the L2HMC algorithm to simulations in lattice QCD.

Boltzmann Machines in TensorFlow with examples

Pieces of code that have appeared on my blog with a focus on stochastic simulations.

General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

Examples for Bayesian inference using DynamicHMC.jl and related packages.

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

A common framework for implementing and using log densities for inference.

The base NIMBLE package for R

Regression with Summary Statistics.

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

Bayesian Generalized Linear Models with Time-Varying Coefficients

Distributed Bayesian Entity Resolution in Apache Spark

Latent Dirichlet Allocation

High-performance Bayesian Data Analysis on the GPU in Clojure

Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States

MCMC sample analysis, kernel densities, plotting, and GUI

A web interface for exploring PyMC3 traces

Documentation, models and code relating to the 3rd edition of the textbook Stochastic Modelling for Systems Biology

Equilibrium Expectation for ERGM parameter estimation for large directed networks

AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)

Implementing MCMC sampling from scratch in R for various Bayesian models

Graphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

The posterior R package

Bayesian methods in deep learning Summer School

Python MCMC Sampler