
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.


coremsg

Scalable-Dynamic-Edge-Partition-Models-with-SG-MCMC


Scalable Dynamic Edge Partition Models with SG-MCMC


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Proposing a novel dynamic edge partition model for temporal networks with scalable inference using SG-MCMC algorithms.


dynamic-edge-partition-models-for-temporal-networks-with-scalable-inference


Dynamic Edge Partition Models for Temporal Networks with Scalable Inference
