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Download the fantastic book titled Foundations of Probabilistic Programming written by Gilles Barthe, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Foundations of Probabilistic Programming", which was released on 03 December 2020. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Foundations of Probabilistic Programming by Gilles Barthe PDF

This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core.

Foundations of Probabilistic Programming

Detail About Foundations of Probabilistic Programming PDF

  • Author : Gilles Barthe
  • Publisher : Cambridge University Press
  • Genre : Computers
  • Total Pages : 583 pages
  • ISBN : 110848851X
  • PDF File Size : 29,8 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Foundations of Probabilistic Programming

Foundations of Probabilistic Programming
  • Publisher : Cambridge University Press
  • File Size : 23,8 Mb
  • Release Date : 03 December 2020
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This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the

Foundations of Probabilistic Logic Programming

Foundations of Probabilistic Logic Programming
  • Publisher : CRC Press
  • File Size : 51,9 Mb
  • Release Date : 01 September 2022
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Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertain information by means of probability theory. Probabilistic Logic Programming is at the intersection of two wider research fields:

Foundations of Probabilistic Logic Programming

Foundations of Probabilistic Logic Programming
  • Publisher : River Publishers
  • File Size : 37,6 Mb
  • Release Date : 01 September 2018
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Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertain information. Probabilistic Logic Programming is at the intersection of two wider research fields: the integration of logic and

Probabilistic Inductive Logic Programming

Probabilistic Inductive Logic Programming
  • Publisher : Springer
  • File Size : 44,8 Mb
  • Release Date : 26 February 2008
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This book provides an introduction to probabilistic inductive logic programming. It places emphasis on the methods based on logic programming principles and covers formalisms and systems, implementations and applications, as

Abstraction, Refinement and Proof for Probabilistic Systems

Abstraction, Refinement and Proof for Probabilistic Systems
  • Publisher : Springer Science & Business Media
  • File Size : 52,8 Mb
  • Release Date : 16 June 2024
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Provides an integrated coverage of random/probabilistic algorithms, assertion-based program reasoning, and refinement programming models, providing a focused survey on probabilistic program semantics. This book illustrates, by examples, the typical

Practical Foundations for Programming Languages

Practical Foundations for Programming Languages
  • Publisher : Cambridge University Press
  • File Size : 29,7 Mb
  • Release Date : 04 April 2016
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This book unifies a broad range of programming language concepts under the framework of type systems and structural operational semantics.

Practical Probabilistic Programming

Practical Probabilistic Programming
  • Publisher : Simon and Schuster
  • File Size : 20,6 Mb
  • Release Date : 29 March 2016
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Summary Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you'll learn how to use the PP paradigm to model application domains and then express those probabilistic

Foundations of Data Science

Foundations of Data Science
  • Publisher : Cambridge University Press
  • File Size : 38,7 Mb
  • Release Date : 23 January 2020
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Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.

Probabilistic Reasoning in Intelligent Systems

Probabilistic Reasoning in Intelligent Systems
  • Publisher : Elsevier
  • File Size : 39,8 Mb
  • Release Date : 28 June 2014
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Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication