Description
Probabilistic Graphical Models, Softcover reprint of the original 1st ed. 2015
Principles and Applications
Advances in Computer Vision and Pattern Recognition Series
Author: Sucar Luis Enrique
Language: EnglishSubjects for Probabilistic Graphical Models:
Support: Print on demand
Description
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Part I: Fundamentals.- Introduction.- Probability Theory.- Graph Theory.- Part II: Probabilistic Models.- Bayesian Classifiers.- Hidden Markov Models.- Markov Random Fields.- Bayesian Networks: Representation and Inference.- Bayesian Networks: Learning.- Dynamic and Temporal Bayesian Networks.- Part III: Decision Models.- Decision Graphs.- Markov Decision Processes.- Part IV: Relational and Causal Models.- Relational Probabilistic Graphical Models.- Graphical Causal Models.