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math.ST2024
Autoregressive networks with dependent edges
Jinyuan Chang, Qin Fang, Eric D. Kolaczyk +2
We propose an autoregressive framework for modelling dynamic networks with dependent edges. It encompasses models that accommodate, for example, transitivity, degree heterogenenity…
stat.ME2024
Stochastic gradient descent-based inference for dynamic network models with attractors
Hancong Pan, Xiaojing Zhu, Cantay Caliskan +4
In Coevolving Latent Space Networks with Attractors (CLSNA) models, nodes in a latent space represent social actors, and edges indicate their dynamic interactions. Attractors are a…