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

PhyML -- Phylogenetic estimation using (Maximum) Likelihood

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

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

A multi-planet Radial Velocity and Transit modelling software

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

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

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

Bayesian Generalized Linear Models with Time-Varying Coefficients

High-performance Bayesian Data Analysis on the GPU in Clojure

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

Equilibrium Expectation for ERGM parameter estimation for large directed networks

Make a sweet giant triangle confusogram (GTC) plot

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Use MCMC to analyze districting plans and gerrymanders

Application of the L2HMC algorithm to simulations in lattice QCD.

Boltzmann Machines in TensorFlow with examples

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

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

Regression with Summary Statistics.

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

Latent Dirichlet Allocation

Distributed Bayesian Entity Resolution in Apache Spark

A web interface for exploring PyMC3 traces

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

Python MCMC Sampler

DynamicHMC versions of StatisticalRethinking models

Bayesian methods in deep learning Summer School

Full Bayesian Inference for Hidden Markov Models

The posterior R package

CmdStanR: the R interface to CmdStan

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

Start with the Chempy tutorial

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

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

Bayesian Data Analysis demos for Python

Material for a workshop on Bayesian stats with R

Bayesian inference with probabilistic programming.

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

RStan, the R interface to Stan

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

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

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

Bitmap generation from a single example with convolutions and MCMC

Nested Sampling post-processing and plotting

The Python ensemble sampling toolkit for affine-invariant MCMC

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

Bayesian Data Analysis demos for R

machine learning

A Bayesian Analysis Toolkit in Julia

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

bayesplot R package for plotting Bayesian models

Blang's software development kit

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

Automatic Reparameterisation of Probabilistic Programs

Turing version of StatisticalRethinking models.

The base NIMBLE package for R

MCMC sample analysis, kernel densities, plotting, and GUI

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

Implementing MCMC sampling from scratch in R for various Bayesian models