Latent Space Models for Multiplex Networks

This lecture by the instructor covers latent space models for multiplex networks with shared structure, focusing on network data representation, probabilistic models for networks, and examples of structural assumptions. The lecture also delves into the stochastic block model, random dot product graph, and generalized random dot product graph. It discusses multiplex networks, problem formulation, and the MultiNeSS model for multiplex networks with shared structure. The lecture concludes with discussions on parameter estimation, identifiability, consistency, and exploratory results on common and individual latent dimensions.