Bayesian Nonparametric Modeling for Clustering Heterogeneous Network Populations

This research introduces a novel Bayesian nonparametric model using a location-scale Dirichlet process mixture of centered Erdős–Rényi kernels to effectively cluster heterogeneous populations of networks, demonstrating superior performance over existing methods in various inferential tasks.