TuringLang/Turing.jl: v0.24.0

Beskrivning

Turing.jl is a Julia library for general-purpose probabilistic programming. Turing allows the user to write models using standard Julia syntax, and provides a wide range of sampling-based inference methods for solving problems across probabilistic machine learning, Bayesian statistics, and data science. Compared to other probabilistic programming languages, Turing has a special focus on modularity, and decouples the modelling language (i.e. the compiler) and inference methods. This modular design, together with the use of a high-level numerical language Julia, makes Turing particularly extensible: new model families and inference methods can be easily added. Current features include: General-purpose probabilistic programming with an intuitive modelling interface Robust, efficient Hamiltonian Monte Carlo (HMC) sampling for differentiable posterior distributions Particle MCMC sampling for complex posterior distributions involving discrete variables and stochastic control flows Compositional inference via Gibbs sampling that combines particle MCMC, HMC, Random-Walk MH (RWMH) and Elliptical Slice Sampling Advanced variational inference based on ADVI and Normalising Flows Getting Started Turing's home page, with links to everything you'll need to use Turing is: https://turing.ml/dev/docs/using-turing/get-started Full description in GitHub: https://github.com/TuringLang/Turing.jl/tree/v0.24.0 The title and description of this software/code correspond with the situation when the software metadata was imported to ACRIS. The most recent version of metadata is available in the original repository.
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Publiceringsår

2022

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Upphovspersoner

Department of Computer Science

Adam Scibior - Upphovsperson

Andreas Noack - Upphovsperson

Arthur Lui - Upphovsperson

Cameron Pfiffer - Upphovsperson

David Widmann - Upphovsperson

Dilum Aluthge - Upphovsperson

Emile Mathieu - Upphovsperson

Emma Smith - Upphovsperson

Hao Zhang - Upphovsperson

Harrison Wilde - Upphovsperson

Hessam Mehr - Upphovsperson

Hong Ge - Upphovsperson

Jonathan D. Trattner - Upphovsperson

Kai Xu - Upphovsperson

Killian Q. Zhuo - Upphovsperson

Kyurae Kim - Upphovsperson

Ludger Paehler - Upphovsperson

Martin Trapp Orcid -palvelun logo - Upphovsperson

Miles Lucas - Upphovsperson

Mohamed Tarek - Upphovsperson

Peifan Wu - Upphovsperson

Philipp Gabler - Upphovsperson

Phillip Alday - Upphovsperson

Pietro Monticone - Upphovsperson

Ramon Diaz-Uriarte - Upphovsperson

Rik Huijzer - Upphovsperson

Saranjeet Kaur - Upphovsperson

Tom Röschinger - Upphovsperson

Tor Erlend Fjelde - Upphovsperson

Will Tebbutt - Upphovsperson

Xianda Sun - Upphovsperson

Brown University - Medarbetare

Max Planck Institute for Astronomy - Medarbetare

TRIUMF - Medarbetare

Technical University of Munich - Medarbetare

Universidad Autónoma de Madrid - Medarbetare

University Medical Center Groningen - Medarbetare

University of Cambridge - Medarbetare

University of Glasgow - Medarbetare

University of Pennsylvania - Medarbetare

Uppsala University - Medarbetare

Zenodo - Utgivare

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Data- och informationsvetenskap

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Creative Commons Attribution 4.0 International (CC BY 4.0)

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