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Innovations in Bayesian Networks

Overview of attention for book
Cover of 'Innovations in Bayesian Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Innovations in Bayesian Networks
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    Chapter 2 A Polemic for Bayesian Statistics
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    Chapter 3 A Tutorial on Learning with Bayesian Networks
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    Chapter 4 The Causal Interpretation of Bayesian Networks
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    Chapter 5 An Introduction to Bayesian Networks and Their Contemporary Applications
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    Chapter 6 Objective Bayesian Nets for Systems Modelling and Prognosis in Breast Cancer
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    Chapter 7 Modeling the Temporal Trend of the Daily Severity of an Outbreak Using Bayesian Networks
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    Chapter 8 An Information-Geometric Approach to Learning Bayesian Network Topologies from Data
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    Chapter 9 Causal Graphical Models with Latent Variables: Learning and Inference
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    Chapter 10 Use of Explanation Trees to Describe the State Space of a Probabilistic-Based Abduction Problem
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    Chapter 11 Toward a Generalized Bayesian Network
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    Chapter 12 A Survey of First-Order Probabilistic Models
Attention for Chapter 10: Use of Explanation Trees to Describe the State Space of a Probabilistic-Based Abduction Problem
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Citations

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Summary Dimensions citations
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Chapter title
Use of Explanation Trees to Describe the State Space of a Probabilistic-Based Abduction Problem
Chapter number 10
Book title
Innovations in Bayesian Networks
Published by
Springer, Berlin, Heidelberg, January 2008
DOI 10.1007/978-3-540-85066-3_10
Book ISBNs
978-3-54-085065-6, 978-3-54-085066-3
Authors

M. Julia Flores, José A. Gámez, Serafín Moral

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Virgin Islands, U.S. 1 14%
Unknown 6 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Professor > Associate Professor 2 29%
Researcher 1 14%
Lecturer 1 14%
Unknown 1 14%
Readers by discipline Count As %
Computer Science 4 57%
Environmental Science 2 29%
Engineering 1 14%

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