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Modeling and reasoning with Bayesian networks
2009, Cambridge University Press
in English
0521884381 9780521884389
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Book Details
Table of Contents
Introduction
Propositional logic
Probability calculus
Bayesian networks
Building Bayesian networks
Inference by variable elimination
Inference by factor elimination
Inference by conditioning
Models for graph decomposition
Most likely instantiations
The complexity of probabilistic inference
Compiling Bayesian networks
Inference with local structure
Approximate inference by belief propagation
Approximate inference by stochastic sampling
Sensitivity analysis
Learning : the maximum likelihood approach
Learning : the Bayesian approach.
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