Nonparametric Bayesian inference of the microcanonical stochastic block model

9 Oct 2016Tiago P. Peixoto

A principled approach to characterize the hidden structure of networks is to formulate generative models, and then infer their parameters from data. When the desired structure is composed of modules or "communities", a suitable choice for this task is the stochastic block model (SBM), where nodes are divided into groups, and the placement of edges is conditioned on the group memberships... (read more)

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