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Innovations in Bayesian Networks

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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 7: Modeling the Temporal Trend of the Daily Severity of an Outbreak Using Bayesian Networks
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