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インサイト - Dynamic Edge Partition Models
Scalable Dynamic Edge Partition Models with SG-MCMC
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.
Dynamic Edge Partition Models for Temporal Networks with Scalable Inference
Proposing a novel dynamic edge partition model for temporal networks with scalable inference using SG-MCMC algorithms.
