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Repeated Motif Hierarchical Stochastic Blockmodels

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SNAW01 - Graph limits and statistics

Co-authors: Vince Lyzinski (Johns Hopkins University), Minh Tang (Johns Hopkins University), Avanti Athreya (Johns Hopkins University), Youngser Park (Johns Hopkins University), Joshua Vogelstein (Johns Hopkins University), Keith Levin (Johns Hopkins University)

Based on our methodology for community detection and community comparison in graphs (Lyzinski et al., 2015,, we formulate a model selection procedure for deciding whether a hierarchical stochastic blockmodel graph supports the conjecture of repeated motifs. Such a graph inference procedure promises to address a fundamental outstanding question regarding the atoms of neural computation (Marcus, Marblestone & Dean, 2014, .
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