Bayesian Programming
1st Edition
Published on 20. December 2013
380 pages
978-1-4398-8033-3 (ISBN)
Description
A new modeling methodology, new inference algorithms, new programming languages, and new hardware are all needed to create a complete Bayesian computing framework. Focusing on the methodology and algorithms, this book describes the first steps toward reaching that goal. It emphasizes probability as an alternative to Boolean logic, covering new methods to build probabilistic programs for real-world applications. The book encourages readers to explore emerging areas and develop new programming languages and hardware architectures. A Python package is available on a supplementary website.
Reviews / Votes
"Bayesian Programming comprises a methodology, a programming language, and a set of tools for developing and applying ... complex models. ... The approach is described in great detail, with many worked examples backed up by an online code repository. Unlike other books that tend to focus almost entirely on mathematics, this one gives equal time to conceptual and methodological guidance for the model-builder. It grapples with the knotty problems that arise in practice, some of which do not yet have clear solutions."-From the Foreword by Stuart Russell, University of California, Berkeley
"The book has many worked examples backed up by an online code repository. The book provides a contibution on conceptual and methodological guidelines for model-builders. The authors discuss the problem how to build a Bayesian computer. The book has an excellent bibliography."
-Nirode C. Mohanty, in Zentralblatt MATH 1281
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Students and researchers in statistics, computer science and related fields.
Illustrations
61 s/w Abbildungen, 5 s/w Tabellen
75 b/w images
File size
7,13 MB
ISBN-13
978-1-4398-8033-3 (9781439880333)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Pierre Bessiere | Emmanuel Mazer | Juan Ahuactzin
Bayesian Programming
Book
01/2023
1st Edition
Chapman & Hall/CRC
€64.00
Shipment within 10-20 days
Pierre Bessiere | Emmanuel Mazer | Juan Ahuactzin
Bayesian Programming
Book
12/2013
1st Edition
Chapman & Hall/CRC
€204.50
Shipment within 15-20 days
Persons
Pierre Bessiere is with CNRS, the French National Centre for Scientific Research. Juan-Manuel Ahuactzin, Kamel Mekhnacha, and Emmanuel Mazer are with Probayes Inc., France.
Content
Introduction. Bayesian Programming Principles: Basic Concepts. Incompleteness and Uncertainty. Description = Specification + Identification. The Importance of Conditional Independence. Bayesian Program = Description + Question. Bayesian Programming Cookbook: Information Fusion. Bayesian Programming with Coherence Variables. Bayesian Programming Subroutines. Bayesian Programming Conditional Statement. Bayesian Programming Iteration. Bayesian Programming Formalism and Algorithms: Bayesian Programming Formalism. Bayesian Models Revisited. Bayesian Inference Algorithms Revisited. Bayesian Learning Revisited. Frequently Asked Questions and Frequently Argued Matter: Frequently Asked Question and Frequently Argued Matter. Glossary. Index.
