Turing Libraries

This page lists all the packages that are part of the The Turing Organization.

Modelling Languages

• DynamicPPL.jl: A domain-specific language and backend for probabilistic programming languages used by Turing.jl.

• JuliaBUGS.jl: JuliaBUGS is a graph-based probabilistic programming language and a component of the Turing ecosystem.

• TuringGLM.jl: A Julia package for Bayesian generalised linear models used for returning an instantiated Turing model using the formula syntax

Markov chain Monte Carlo (MCMC)

• AdvancedHMC.jl: It provides a robust, modular, and efficient implementation of advanced Hamiltonian Monte Carlo (HMC) algorithms.

• AbstractMCMC.jl: Abstract types and interfaces for Markov chain Monte Carlo methods. This defines an interface for sampling and combining Markov chains.

• ThermodynamicIntegration.jl: A simple package to compute Thermodynamic Integration for computing the evidence in a Bayesian setting.

• AdvancedPS.jl: This is a lightweight package that implements particle-based Monte Carlo algorithms for the Turing ecosystem.

• SliceSampling.jl: This package is a collection of slice sampling algorithms including the univariate slice samplers by Neal (2003).

• EllipticalSliceSampling.jl: This package implements elliptical slice sampling in the Julia language, as described in Murray, Adams & MacKay (2010).

• NestedSamplers.jl: A Julian implementation of single- and multi-ellipsoidal nested sampling algorithms using the AbstractMCMC interface.

Diagnostics

• MCMCChains.jl: Implementation of Julia types for summarising MCMC simulations and utility functions for diagnostics and visualisations.

• MCMCDiagnosticTools.jl: This package provides functionality for diagnosing samples generated using Markov Chain Monte Carlo.

• ParetoSmooth.jl: An implementation of Pareto smoothed importance sampling(PSIS) algorithms in Julia.

Bijectors.jl

• Bijectors.jl: A package for transforming distributions, used by Turing.jl.

TuringCallbacks.jl

• TuringCallbacks.jl: A package containing some convenient callbacks to use when you sample in Turing.jl.

TuringBenchmarking.jl

• TuringBenchmarking.jl: A package for benchmarking and checking Turing.jl models.

Gaussian Processes

• AbstractGPs.jl: AbstractGPs.jl is a package that defines a low-level API for working with Gaussian processes (GPs), and basic functionality for working with them in the simplest cases.

• KernelFunctions.jl: Julia package for kernel functions for machine learning.

• ApproximateGPs.jl: This is a package that provides some approximate inference algorithms for Gaussian process models, built on top of AbstractGPs.jl.