Multiscale Euclidean Network Trajectories: Second-Moment Geometry, Attribution, and Change Points

ArXi:2605.04589v1 Announce Type: cross A central challenge in dynamic network analysis is to represent temporal evolution in a way that is both geometrically meaningful and statistically identifiable. One approach embeds a sequence of network snapshots as trajectories in a Euclidean space and relates these trajectories to node embeddings. In multilayer and unfolded spectral constructions, however, node embeddings and their underlying latent positions are identifiable only up to general linear transformations.