2 papers
stat.AP2026
Integrative Learning of Dynamically Evolving Multiplex Graphs and Nodal Attributes Using Neural Network Gaussian Processes with an Application to Dynamic Terrorism Graphs
Jose Rodriguez-Acosta, Sharmistha Guha, Lekha Patel +1
Exploring the dynamic co-evolution of multiplex graphs and nodal attributes is a compelling question in criminal and terrorism networks. This article is motivated by the study of d…
stat.ME2026
Simultaneous global and local clustering in multiplex networks with covariate information
Joshua Corneck, Edward A. K. Cohen, James S. Martin +3
Understanding both global and layer-specific group structures is useful for uncovering complex patterns in networks with multiple interaction types. In this work, we introduce a ne…