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Books Books 1 - 10 of about 45 related to Modeling and Reasoning with Bayesian Networks.   

Modeling and Reasoning with Bayesian Networks

Adnan Darwiche - Computers - 2009 - 548 pages
This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for ...
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Artificial Intelligence: Foundations of Computational Agents

David L. Poole, Alan K. Mackworth - Computers - 2010
Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This textbook, aimed at junior to senior undergraduate ...
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Bayesian Networks: An Introduction

Timo Koski, John Noble - Mathematics - 2011 - 366 pages
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for ...
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Learning in Graphical Models

M.I. Jordan - Computers - 2012 - 630 pages
In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points ...
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Judea Pearl - Computers - 2014 - 552 pages
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning ...
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Probabilistic Graphical Models: Principles and Applications

Luis Enrique Sucar - Computers - 2015 - 253 pages
This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. The book covers the fundamentals for ...
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Constraint Processing

Rina Dechter - Computers - 2003 - 480 pages
Constraint satisfaction is a simple but powerful tool. Constraints identify the impossible and reduce the realm of possibilities to effectively focus on the possible, allowing ...
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Bayesian Reasoning and Machine Learning

David Barber - Computers - 2012
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including ...
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Probabilistic Methods for Bioinformatics: with an Introduction to Bayesian ...

Richard E. Neapolitan - Computers - 2009 - 424 pages
The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with ...
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