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questions in the context of the stochastic block model. the stochastic block model (sbm) has been used widely as a canonical model for community detection. it is arguably the simplest model of a graph with communities (see de nitions in the next section). since the sbm is
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in the context of the stochastic block model. the stochastic block model (sbm) has been used widely as a canonical model for community detection. it is arguably the simplest model of a graph with communities (see de nitions in the next section). since the sbm is a generative model for the data, it bene ts from a ground truth for the communities
the stochastic block model (sbm) is a random graph model with planted clusters. it is widely employed as a canonical model to study clustering and community detection, and machine learning and information theory, a review article for the information theory newsletter, and
this sbm-based machine learning model is more efficient, cost-effective and safer compared to other approaches. mri provides useful information on the structural and functional organization of the cerebral cortex. sbm is a well-established structural mri technique used for the detection of between-group differences at the whole-brain level [37,38].
block model” (sbm) (26) can be used to model the presence of a seed set in the graph, allowing us to derive principled methods for ranking nodes in the space of landing probabilities. we focus on a two-block sbm, where one block of nodes corresponds to the community of a labeled seed set, whereas the other block
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