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DOI: 10.4230/LIPIcs.CALCO.2017.25

The EfProb Library for Probabilistic Calculations

Authors: Kenta Cho and Bart Jacobs

Published in: LIPIcs, Volume 72, 7th Conference on Algebra and Coalgebra in Computer Science (CALCO 2017)

Abstract

EfProb is an abbreviation of Effectus Probability. It is the name of a library for probability calculations in Python. EfProb offers a uniform language for discrete, continuous and quantum probability. For each of these three cases, the basic ingredients of the language are states, predicates, and channels. Probabilities are typically calculated as validities of predicates in states. States can be updated (conditioned) with predicates. Channels can be used for state transformation and for predicate transformation. This short paper gives an overview of the use of EfProb.

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Kenta Cho and Bart Jacobs. The EfProb Library for Probabilistic Calculations. In 7th Conference on Algebra and Coalgebra in Computer Science (CALCO 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 72, pp. 25:1-25:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{cho_et_al:LIPIcs.CALCO.2017.25,
  author =	{Cho, Kenta and Jacobs, Bart},
  title =	{{The EfProb Library for Probabilistic Calculations}},
  booktitle =	{7th Conference on Algebra and Coalgebra in Computer Science (CALCO 2017)},
  pages =	{25:1--25:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-033-0},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{72},
  editor =	{Bonchi, Filippo and K\"{o}nig, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CALCO.2017.25},
  URN =		{urn:nbn:de:0030-drops-80529},
  doi =		{10.4230/LIPIcs.CALCO.2017.25},
  annote =	{Keywords: probability, embedded language, effectus theory}
}

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The EfProb Library for Probabilistic Calculations

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