ABSTRACT
In many practical applications such as social network analysis, reverse-engineering of gene networks, or discovering functional brain connectivity patterns, just to name a few, the ultimate objective is to reconstruct underlying dependencies among the variables of interest, such as individuals, genes, or brain areas. Probabilistic graphical models provide a convenient visualization and inference tool that captures statistical dependencies among random variables explicitly in a form of a graph.
