Probabilistic Graphical Models : Principles and Applications (Paperback, Softcover reprint of the original 1st ed. 2015)

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