Introduces TSBM, a new Bayesian model for directed networks that enforces ordered blocks via transitivity-inducing priors on directional imbalance and jointly infers block count with an age-ordered partition prior.
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Characterizes the distributional mean-field limit of co-evolving latent space networks with feedback, including empirical measures and graphon convergence, via a conditional propagation of chaos result.
Generalizes L-Modularity into a unified framework for community detection in complex link streams that include delayed, directed, weighted, and multipartite interactions.
citing papers explorer
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Ordering Stochastic Block Models via prior transitivity
Introduces TSBM, a new Bayesian model for directed networks that enforces ordered blocks via transitivity-inducing priors on directional imbalance and jointly infers block count with an age-ordered partition prior.
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Mean-Field Analysis of Latent Variable Process Models on Dynamically Evolving Graphs with Feedback Effects
Characterizes the distributional mean-field limit of co-evolving latent space networks with feedback, including empirical measures and graphon convergence, via a conditional propagation of chaos result.
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Generalized L-Modularity for Community Detection Beyond Simple Temporal Networks
Generalizes L-Modularity into a unified framework for community detection in complex link streams that include delayed, directed, weighted, and multipartite interactions.