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Advances in Probabilistic Graphical Models

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Cover of 'Advances in Probabilistic Graphical Models'

Table of Contents

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    Book Overview
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    Chapter 1 Markov Equivalence in Bayesian Networks
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    Chapter 2 A Causal Algebra for Dynamic Flow Networks
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    Chapter 3 Graphical and Algebraic Representatives of Conditional Independence Models
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    Chapter 4 Bayesian Network Models with Discrete and Continuous Variables
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    Chapter 5 Sensitivity Analysis of Probabilistic Networks
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    Chapter 6 A Review on Distinct Methods and Approaches to Perform Triangulation for Bayesian Networks
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    Chapter 7 Decisiveness in Loopy Propagation
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    Chapter 8 Lazy Inference in Multiply Sectioned Bayesian Networks Using Linked Junction Forests
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    Chapter 9 A Study on the Evolution of Bayesian Network Graph Structures
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    Chapter 10 Learning Bayesian Networks with an Approximated MDL Score
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    Chapter 11 Learning of Latent Class Models by Splitting and Merging Components
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    Chapter 12 An Efficient Exhaustive Anytime Sampling Algorithm for Influence Diagrams
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    Chapter 13 Multi-currency Influence Diagrams
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    Chapter 14 Parallel Markov Decision Processes
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    Chapter 15 Applications of HUGIN to Diagnosis and Control of Autonomous Vehicles
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    Chapter 16 Biomedical Applications of Bayesian Networks
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    Chapter 17 Learning and Validating Bayesian Network Models of Gene Networks
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    Chapter 18 The Role of Background Knowledge in Bayesian Classification
Overall attention for this book and its chapters
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51 Mendeley
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Title
Advances in Probabilistic Graphical Models
Published by
Springer Berlin Heidelberg, June 2007
DOI 10.1007/978-3-540-68996-6
ISBNs
978-3-54-068994-2, 978-3-54-068996-6
Editors

Lucas, Peter, Gámez, José A., Salmerón, Antonio

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
United States 1 2%
China 1 2%
France 1 2%
Unknown 47 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 33%
Researcher 11 22%
Student > Master 7 14%
Professor > Associate Professor 4 8%
Student > Bachelor 2 4%
Other 10 20%
Readers by discipline Count As %
Computer Science 13 25%
Engineering 12 24%
Mathematics 6 12%
Agricultural and Biological Sciences 3 6%
Economics, Econometrics and Finance 2 4%
Other 15 29%

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