Parameter estimation in interacting particle systems on dynamic random networks

In this paper we consider a class of interacting particle systems on dynamicrandom networks, in which the joint dynamics of vertices and edges acts asone-way feedback, i.e., edges appear and disappear over time depending on thestate of the two connected vertices, while the vertex dynamics does not dependon the edge process. Our goal is to estimate the underlying dynamics frompartial information of the process, specifically from snapshots of the totalnumber of edges present. We showcase the effectiveness of our inference methodthrough various numerical results.