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A random effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging

A random effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging

To analyze data from multisubject experiments in neuroimaging studies, we develop a modeling framework for joint community detection in a group of related networks that can be considered as a sample from a population of networks. The proposed random effects stochastic block model facilitates the study of group differences and …