Article

Probabilistic programming in Anglican

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ECMLPKDD'15: Proceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III

Pages 308 - 311

https://doi.org/10.1007/978-3-319-23461-8_36

Published: 07 September 2015 Publication History

Abstract

Anglican is a probabilistic programming system designed to interoperate with Clojure and other JVM languages. We describe the implementation of Anglican and illustrate how its design facilitates both explorative and industrial use of probabilistic programming.

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Cited By

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Wang PYang TFu HLi GOng C(2024)Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial SolvingProceedings of the ACM on Programming Languages10.1145/36564328:PLDI(1361-1386)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3656432
Grohe MKaminski BKatoen JLindner P(2022)Generative Datalog with Continuous DistributionsJournal of the ACM10.1145/355910269:6(1-52)Online publication date: 30-Aug-2022
https://dl.acm.org/doi/10.1145/3559102
Grohe MLindner P(2022)Independence in Infinite Probabilistic DatabasesJournal of the ACM10.1145/354952569:5(1-42)Online publication date: 10-Aug-2022
https://dl.acm.org/doi/10.1145/3549525
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Information

Published In

ECMLPKDD'15: Proceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III

September 2015

340 pages

ISBN:9783319234601

Editors:
Albert Bifet
Huawei Noah's Ark Lab, Shatin, Hong Kong SAR
,
Michael May
Siemens AG Corporate Technology, München, Germany
,
Bianca Zadrozny
IBM Research Brazil, Rio de Janeiro, Brazil
,
Ricard Gavalda
Universitat Politècnica de Catalunya, Barcelona, Spain
,
Dino Pedreschi
Università di Pisa, Pisa, Italy

Publisher

Springer

Gewerbestrasse 11 CH-6330, Cham (ZG), Switzerland

Publication History

Published: 07 September 2015

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Probabilistic programming

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Cited By

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Wang PYang TFu HLi GOng C(2024)Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial SolvingProceedings of the ACM on Programming Languages10.1145/36564328:PLDI(1361-1386)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3656432
Grohe MKaminski BKatoen JLindner P(2022)Generative Datalog with Continuous DistributionsJournal of the ACM10.1145/355910269:6(1-52)Online publication date: 30-Aug-2022
https://dl.acm.org/doi/10.1145/3559102
Grohe MLindner P(2022)Independence in Infinite Probabilistic DatabasesJournal of the ACM10.1145/354952569:5(1-42)Online publication date: 10-Aug-2022
https://dl.acm.org/doi/10.1145/3549525
Beutner ROng CZaiser FJhala RDillig I(2022)Guaranteed bounds for posterior inference in universal probabilistic programmingProceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation10.1145/3519939.3523721(536-551)Online publication date: 9-Jun-2022
https://dl.acm.org/doi/10.1145/3519939.3523721
Beutner ROng LFreund SYahav E(2021)On probabilistic termination of functional programs with continuous distributionsProceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation10.1145/3453483.3454111(1312-1326)Online publication date: 19-Jun-2021
https://dl.acm.org/doi/10.1145/3453483.3454111
Dal Lago UFaggian CRocca S(2021)Intersection types and (positive) almost-sure terminationProceedings of the ACM on Programming Languages10.1145/34343135:POPL(1-32)Online publication date: 4-Jan-2021
https://dl.acm.org/doi/10.1145/3434313
Borghouts JGordon ASarkar AToronto N(2019)End-User Probabilistic ProgrammingQuantitative Evaluation of Systems10.1007/978-3-030-30281-8_1(3-24)Online publication date: 10-Sep-2019
https://dl.acm.org/doi/10.1007/978-3-030-30281-8_1
Mansinghka VSchaechtle UHanda SRadul AChen YRinard M(2018)Probabilistic programming with programmable inferenceACM SIGPLAN Notices10.1145/3296979.319240953:4(603-616)Online publication date: 11-Jun-2018
https://dl.acm.org/doi/10.1145/3296979.3192409
Mansinghka VSchaechtle UHanda SRadul AChen YRinard MFoster JGrossman D(2018)Probabilistic programming with programmable inferenceProceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation10.1145/3192366.3192409(603-616)Online publication date: 11-Jun-2018
https://dl.acm.org/doi/10.1145/3192366.3192409
Tolpin Dvan de Meent JYang HWood FSchrijvers T(2016)Design and Implementation of Probabilistic Programming Language AnglicanProceedings of the 28th Symposium on the Implementation and Application of Functional Programming Languages10.1145/3064899.3064910(1-12)Online publication date: 31-Aug-2016
https://dl.acm.org/doi/10.1145/3064899.3064910

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