Turing Libraries
This page lists all the packages that are part of the The Turing Organisation, and provides links to their respective API documentation pages and GitHub repositories.
If you are looking for tutorials and usage guides, please visit this page.
Turing.jl itself
Modelling Languages
DynamicPPL | API | GitHub | Domain-specific language and backend for probabilistic programming; contains the core functionality of Turing.jl |
JuliaBUGS | API | GitHub | A graph-based probabilistic programming language |
TuringGLM | API | GitHub | Bayesian generalised linear models used for returning an instantiated Turing model using the formula syntax |
AbstractPPL | API | GitHub | An abstract interface for probabilistic programming languages |
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Markov Chain Monte Carlo (MCMC)
AbstractMCMC | API | GitHub | Abstract types and interfaces for Markov chain Monte Carlo methods, featuring progress bars, parallel sampling, and user-defined callbacks |
AdvancedHMC | API | GitHub | A robust, modular, and efficient implementation of advanced Hamiltonian Monte Carlo algorithms |
AdvancedMH | API | GitHub | Random walk and adaptive Metropolis–Hastings algorithms |
AdvancedPS | API | GitHub | Lightweight implementation of particle-based Monte Carlo algorithms |
SliceSampling | API | GitHub | Univariate and multivariate slice sampling algorithms |
EllipticalSliceSampling | API | GitHub | Elliptical slice sampling for inference in models with multivariate Gaussian priors |
NestedSamplers | API | GitHub | Single- and multi-ellipsoidal nested sampling algorithms |
ThermodynamicIntegration | API | GitHub | Computing Bayesian evidence using thermodynamic integration |
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Variational Inference
Utilities
Diagnostics
MCMCChains | API | GitHub | Implementation of the Chains type returned by Turing sampling, with functions for diagnostics and visualisations |
MCMCDiagnosticTools | API | GitHub | Extra functionality for diagnosing samples generated with MCMC methods |
ParetoSmooth | API | GitHub | Leave-one-out cross-validation for fitted Bayesian models using Pareto smoothed importance sampling |
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Distributions
Infrastructure
Gaussian Processes
The following packages come under the umbrella of the JuliaGaussianProcesses organisation.
AbstractGPs | API | GitHub | Low-level API and basic functionality for working with Gaussian processes |
KernelFunctions | API | GitHub | Kernel functions for machine learning |
ApproximateGPs | API | GitHub | Approximate inference algorithms for Gaussian process models |
GPLikelihoods | API | GitHub | Likelihoods used as building blocks in non-Gaussian problems |
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