Bayesian inference with probabilistic programming.

Probabilistic programming via source rewriting

Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.

A Bayesian Analysis Toolkit in Julia

Bayesian Statistics using Julia and Turing

Bayesian Generalized Linear models using `@formula` syntax.

WIP successor to Soss.jl

Transformations to contrained variables from ℝⁿ.

Markov Chain Monte Carlo convergence diagnostics in Julia

Graphical tools for Bayesian inference and posterior predictive checks

Bayesian inference on wiring diagrams.

Particle-based and nonparametric variational methods for approximate Bayesian inference and Probabilistic Programming

Metric Gaussian Variational Inference

Toolkit functions and example outputs for Bayesian (Structural) Vector Autoregressive (VAR) models

Statistical analyses for Bayesian workflows

Julia package to perform Bayesian clustering of high-dimensional Euclidean data using pairwise dissimilarity information.

Interface between Turing.jl and MonteCarloMeasurements.jl

A Julia Package for Bayesian Nonparametric Analysis for Machine Learning

Bayesian Integration of functions

BayesBase is a package that serves as an umbrella, defining, exporting, and re-exporting methods essential for Bayesian statistics