Rylan Schaeffer

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Probabilistic Graphical Models

Overview

A joint distribution over \(N\) variables \(\underline{x}\) can permit complicated relationships between the variables. One general principle is that performing inference becomes easier in the absence of relationships between variables. This motivates us to specify relationships between variables as a graphs and then use the graph structure to design efficient inference algorithms.