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@@ -1,61 +1,114 @@ | ||
--- | ||
title: "Turing Libraries" | ||
page-layout: full | ||
search: false | ||
toc: false | ||
include-in-header: | ||
- text: | | ||
<style>a {text-decoration: none;}a:hover {text-decoration: underline;}</style> | ||
listing: | ||
- id: libraries-main | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: main | ||
- id: libraries-modelling | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: modelling | ||
- id: libraries-mcmc | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: mcmc | ||
- id: libraries-vi | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: vi | ||
- id: libraries-utilities | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: utilities | ||
- id: libraries-diagnostics | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: diagnostics | ||
- id: libraries-distributions | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: distributions | ||
- id: libraries-infrastructure | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: infrastructure | ||
- id: libraries-gps | ||
template: table.ejs | ||
contents: main.yml | ||
field-required: [name, api, github, description, category] | ||
include: | ||
category: gps | ||
--- | ||
|
||
This page lists all the packages that are part of the [The Turing Organization](https://github.com/TuringLang). | ||
This page lists all the packages that are part of the [The Turing Organisation](https://github.com/TuringLang), and provides links to their respective API documentation pages and GitHub repositories. | ||
|
||
## Modelling Languages | ||
|
||
- [DynamicPPL.jl](https://turinglang.org/DynamicPPL.jl/): A domain-specific language and backend for probabilistic programming languages used by Turing.jl. | ||
If you are looking for tutorials and usage guides, please visit [this page](https://turinglang.org/docs/). | ||
|
||
- [JuliaBUGS.jl](https://turinglang.org/JuliaBUGS.jl/): JuliaBUGS is a graph-based probabilistic programming language and a component of the Turing ecosystem. | ||
## Turing.jl itself | ||
|
||
- [TuringGLM.jl](https://turinglang.org/TuringGLM.jl/): A Julia package for Bayesian generalised linear models used for returning an instantiated Turing model using the formula syntax | ||
::: {#libraries-main} | ||
::: | ||
|
||
## Markov chain Monte Carlo (MCMC) | ||
## Modelling Languages | ||
|
||
- [AdvancedHMC.jl](https://turinglang.org/AdvancedHMC.jl/): It provides a robust, modular, and efficient implementation of advanced Hamiltonian Monte Carlo (HMC) algorithms. | ||
::: {#libraries-modelling} | ||
::: | ||
|
||
- [AbstractMCMC.jl](https://turinglang.org/AbstractMCMC.jl/): Abstract types and interfaces for Markov chain Monte Carlo methods. This defines an interface for sampling and combining Markov chains. | ||
## Markov Chain Monte Carlo (MCMC) | ||
|
||
- [ThermodynamicIntegration.jl](https://github.com/theogf/ThermodynamicIntegration.jl): A simple package to compute Thermodynamic Integration for computing the evidence in a Bayesian setting. | ||
::: {#libraries-mcmc} | ||
::: | ||
|
||
- [AdvancedPS.jl](https://turinglang.org/AdvancedPS.jl/): This is a lightweight package that implements particle-based Monte Carlo algorithms for the [Turing](https://turinglang.org/) ecosystem. | ||
## Variational Inference | ||
|
||
- [SliceSampling.jl](https://turinglang.org/SliceSampling.jl): This package is a collection of slice sampling algorithms including the univariate slice samplers by [Neal (2003)](https://arxiv.org/abs/physics/0009028). | ||
::: {#libraries-vi} | ||
::: | ||
|
||
- [EllipticalSliceSampling.jl](https://turinglang.org/EllipticalSliceSampling.jl/): This package implements elliptical slice sampling in the Julia language, as described in [Murray, Adams & MacKay (2010)](http://proceedings.mlr.press/v9/murray10a/murray10a.pdf). | ||
## Utilities | ||
|
||
- [NestedSamplers.jl](https://turinglang.org/NestedSamplers.jl/): A Julian implementation of single- and multi-ellipsoidal nested sampling algorithms using the [AbstractMCMC](https://github.com/turinglang/abstractmcmc.jl) interface. | ||
::: {#libraries-utilities} | ||
::: | ||
|
||
## Diagnostics | ||
|
||
- [MCMCChains.jl](https://turinglang.org/MCMCChains.jl/): Implementation of Julia types for summarising MCMC simulations and utility functions for [diagnostics](https://turinglang.org/MCMCChains.jl/stable/diagnostics/#Diagnostics) and [visualisations](https://turinglang.org/MCMCChains.jl/stable/statsplots/#StatsPlots.jl). | ||
|
||
- [MCMCDiagnosticTools.jl](https://turinglang.org/MCMCDiagnosticTools.jl/): This package provides functionality for diagnosing samples generated using Markov Chain Monte Carlo. | ||
::: {#libraries-diagnostics} | ||
::: | ||
|
||
- [ParetoSmooth.jl](https://turinglang.org/ParetoSmooth.jl/): An implementation of Pareto smoothed importance sampling(PSIS) algorithms in Julia. | ||
## Distributions | ||
|
||
## Bijectors.jl | ||
::: {#libraries-distributions} | ||
::: | ||
|
||
- [Bijectors.jl](https://turinglang.org/Bijectors.jl/): A package for transforming distributions, used by [Turing.jl](https://github.com/TuringLang/Turing.jl). | ||
## Infrastructure | ||
|
||
## TuringCallbacks.jl | ||
|
||
- [TuringCallbacks.jl](https://turinglang.org/TuringCallbacks.jl/): A package containing some convenient callbacks to use when you sample in [`Turing.jl`](https://app.codecov.io/gh/TuringLang/Turing.jl). | ||
|
||
## TuringBenchmarking.jl | ||
|
||
- [TuringBenchmarking.jl](https://turinglang.org/TuringBenchmarking.jl/): A package for benchmarking and checking [`Turing.jl`](https://github.com/TuringLang/Turing.jl) models. | ||
::: {#libraries-infrastructure} | ||
::: | ||
|
||
## Gaussian Processes | ||
|
||
- [AbstractGPs.jl](https://juliagaussianprocesses.github.io/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](https://juliagaussianprocesses.github.io/KernelFunctions.jl): Julia package for kernel functions for machine learning. | ||
The following packages come under the umbrella of the [JuliaGaussianProcesses organisation](https://github.com/JuliaGaussianProcesses). | ||
|
||
- [ApproximateGPs.jl](https://juliagaussianprocesses.github.io/ApproximateGPs.jl): This is a package that provides some approximate inference algorithms for Gaussian process models, built on top of [AbstractGPs.jl](https://github.com/JuliaGaussianProcesses/AbstractGPs.jl). | ||
::: {#libraries-gps} | ||
::: |
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@@ -0,0 +1,153 @@ | ||
- name: Turing | ||
api: https://turinglang.org/Turing.jl/ | ||
github: https://github.com/TuringLang/Turing.jl | ||
description: "The main entry point to the Turing ecosystem" | ||
category: main | ||
|
||
- name: DynamicPPL | ||
api: https://turinglang.org/DynamicPPL.jl/ | ||
github: https://github.com/TuringLang/DynamicPPL.jl | ||
description: "Domain-specific language and backend for probabilistic programming; contains the core functionality of Turing.jl" | ||
category: modelling | ||
- name: JuliaBUGS | ||
api: https://turinglang.org/JuliaBUGS.jl/ | ||
github: https://github.com/TuringLang/JuliaBUGS.jl | ||
description: "A graph-based probabilistic programming language" | ||
category: modelling | ||
- name: TuringGLM | ||
api: https://turinglang.org/TuringGLM.jl/ | ||
github: https://github.com/TuringLang/TuringGLM.jl | ||
description: "Bayesian generalised linear models used for returning an instantiated Turing model using the formula syntax" | ||
category: modelling | ||
- name: AbstractPPL | ||
api: https://turinglang.org/AbstractPPL.jl/ | ||
github: https://github.com/TuringLang/AbstractPPL.jl | ||
description: "An abstract interface for probabilistic programming languages" | ||
category: modelling | ||
|
||
- name: AbstractMCMC | ||
api: https://turinglang.org/AbstractMCMC.jl/ | ||
github: https://github.com/TuringLang/AbstractMCMC.jl | ||
description: "Abstract types and interfaces for Markov chain Monte Carlo methods, featuring progress bars, parallel sampling, and user-defined callbacks" | ||
category: mcmc | ||
- name: AdvancedHMC | ||
api: https://turinglang.org/AdvancedHMC.jl/ | ||
github: https://github.com/TuringLang/AdvancedHMC.jl | ||
description: "A robust, modular, and efficient implementation of advanced Hamiltonian Monte Carlo algorithms" | ||
category: mcmc | ||
- name: AdvancedMH | ||
api: https://turinglang.org/AdvancedMH.jl/ | ||
github: https://github.com/TuringLang/AdvancedMH.jl | ||
description: "Random walk and adaptive Metropolis–Hastings algorithms" | ||
category: mcmc | ||
- name: AdvancedPS | ||
api: https://turinglang.org/AdvancedPS.jl/ | ||
github: https://github.com/TuringLang/AdvancedPS.jl | ||
description: "Lightweight implementation of particle-based Monte Carlo algorithms" | ||
category: mcmc | ||
- name: SliceSampling | ||
api: https://turinglang.org/SliceSampling.jl/ | ||
github: https://github.com/TuringLang/SliceSampling.jl | ||
description: "Univariate and multivariate slice sampling algorithms" | ||
category: mcmc | ||
- name: EllipticalSliceSampling | ||
api: https://turinglang.org/EllipticalSliceSampling.jl/ | ||
github: https://github.com/TuringLang/EllipticalSliceSampling.jl | ||
description: "Elliptical slice sampling for inference in models with multivariate Gaussian priors" | ||
category: mcmc | ||
- name: NestedSamplers | ||
api: https://turinglang.org/NestedSamplers.jl/ | ||
github: https://github.com/TuringLang/NestedSamplers.jl | ||
description: "Single- and multi-ellipsoidal nested sampling algorithms" | ||
category: mcmc | ||
- name: ThermodynamicIntegration | ||
api: https://theogf.github.io/ThermodynamicIntegration.jl/ | ||
github: https://github.com/theogf/ThermodynamicIntegration.jl | ||
description: "Computing Bayesian evidence using thermodynamic integration" | ||
category: mcmc | ||
|
||
- name: AdvancedVI | ||
api: https://turinglang.org/AdvancedVI.jl/ | ||
github: https://github.com/TuringLang/AdvancedVI.jl | ||
description: "Variational inference algorithms for Bayesian models" | ||
category: vi | ||
- name: NormalizingFlows | ||
api: https://turinglang.org/NormalizingFlows.jl/ | ||
github: https://github.com/TuringLang/NormalizingFlows.jl | ||
description: "Variational inference and normalizing flows for Bayesian computation" | ||
category: vi | ||
|
||
- name: TuringCallbacks | ||
api: https://turinglang.org/TuringCallbacks.jl/ | ||
github: https://github.com/TuringLang/TuringCallbacks.jl | ||
description: "Convenient callbacks for sampling in Turing.jl" | ||
category: utilities | ||
- name: TuringBenchmarking | ||
api: https://turinglang.org/TuringBenchmarking.jl/ | ||
github: https://github.com/TuringLang/TuringBenchmarking.jl | ||
description: "Tools to benchmark and check Turing models" | ||
category: utilities | ||
|
||
- name: MCMCChains | ||
api: https://turinglang.org/MCMCChains.jl/ | ||
github: https://github.com/TuringLang/MCMCChains.jl | ||
description: "Implementation of the Chains type returned by Turing sampling, with functions for diagnostics and visualisations" | ||
category: diagnostics | ||
- name: MCMCDiagnosticTools | ||
api: https://turinglang.org/MCMCDiagnosticTools.jl/ | ||
github: https://github.com/TuringLang/MCMCDiagnosticTools.jl | ||
description: "Extra functionality for diagnosing samples generated with MCMC methods" | ||
category: diagnostics | ||
- name: ParetoSmooth | ||
api: https://turinglang.org/ParetoSmooth.jl/ | ||
github: https://github.com/TuringLang/ParetoSmooth.jl | ||
description: "Leave-one-out cross-validation for fitted Bayesian models using Pareto smoothed importance sampling" | ||
category: diagnostics | ||
|
||
- name: Bijectors | ||
api: https://turinglang.org/Bijectors.jl/ | ||
github: https://github.com/TuringLang/Bijectors.jl | ||
description: "Transformations for distributions" | ||
category: distributions | ||
- name: DistributionsAD | ||
api: https://turinglang.org/DistributionsAD.jl/ | ||
github: https://github.com/TuringLang/DistributionsAD.jl | ||
description: "Automatic differentiation for calculating the log probability densities of distributions" | ||
category: distributions | ||
|
||
- name: turinglang.github.io | ||
api: "" | ||
github: https://github.com/TuringLang/turinglang.github.io | ||
description: "The code for this website itself" | ||
category: infrastructure | ||
- name: docs | ||
api: "" | ||
github: https://github.com/TuringLang/docs | ||
description: "The tutorials and usage guides; any page whose URL begins with https://turinglang.org/docs is built here" | ||
category: infrastructure | ||
- name: actions | ||
api: "" | ||
github: https://github.com/TuringLang/actions | ||
description: "Shared GitHub Actions for the TuringLang organisation" | ||
category: infrastructure | ||
|
||
- name: AbstractGPs | ||
api: https://juliagaussianprocesses.github.io/AbstractGPs.jl | ||
github: https://github.com/JuliaGaussianProcesses/AbstractGPs.jl | ||
description: "Low-level API and basic functionality for working with Gaussian processes" | ||
category: gps | ||
- name: KernelFunctions | ||
api: https://juliagaussianprocesses.github.io/KernelFunctions.jl | ||
github: https://github.com/JuliaGaussianProcesses/KernelFunctions.jl | ||
description: "Kernel functions for machine learning" | ||
category: gps | ||
- name: ApproximateGPs | ||
api: https://juliagaussianprocesses.github.io/ApproximateGPs.jl | ||
github: https://github.com/JuliaGaussianProcesses/ApproximateGPs.jl | ||
description: "Approximate inference algorithms for Gaussian process models" | ||
category: gps | ||
- name: GPLikelihoods | ||
api: https://juliagaussianprocesses.github.io/GPLikelihoods.jl | ||
github: https://github.com/JuliaGaussianProcesses/GPLikelihoods.jl | ||
description: "Likelihoods used as building blocks in non-Gaussian problems" | ||
category: gps |
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<table width="100%"> | ||
<tbody> | ||
<% for (const item of items) { %> | ||
<tr> | ||
<td style="padding: 5px 5px 5px 0"><span style="font-weight: bold"><%- item.name %></span></td> | ||
<% if (item.api !== "") { %> | ||
<td style="padding: 5px 5px"><a href="<%- item.api %>" target="_blank">API</a></td> | ||
<% } %> | ||
<td style="padding: 5px 5px"><a href="<%- item.github %>" target="_blank">GitHub</a></td> | ||
<td style="padding: 5px 0 5px 5px"><%- item.description %></td> | ||
</tr> | ||
<% } %> | ||
</tbody> | ||
</table> |
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@@ -18,4 +18,4 @@ listing: | |
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::: {#team-data} | ||
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::: | ||
::: |
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