Spectral clustering of time-evolving networks using the inflated dynamic
Laplacian for graphs
Spectral clustering of time-evolving networks using the inflated dynamic
Laplacian for graphs
Complex time-varying networks are prominent models for a wide variety of spatiotemporal phenomena. The functioning of networks depends crucially on their connectivity, yet reliable techniques for determining communities in spacetime networks remain elusive. We adapt successful spectral techniques from continuous-time dynamics on manifolds to the graph setting to fill this …