The author proposes a novel dynamic edge partition model that extends the gamma process edge partition model to capture temporal assortative graphs. The approach involves using Dirichlet Markov chains and hierarchical beta-gamma priors for scalable inference.
Proposing a novel dynamic edge partition model for temporal networks with scalable inference using SG-MCMC algorithms.