Scalable Continuous-time Diffusion Framework for Network Inference and Influence Estimation

arXiv:2403.02867v1 Announce Type: cross
Abstract: The study of continuous-time information diffusion has been an important area of research for many applications in recent years. When only the diffusion traces (cascades) are accessible, cascade-based network inference and influence estimation are two essential problems to explore. Alas, existing methods exhibit limited capability to infer and process networks with more than a few thousand nodes, suffering from scalability issues. In this paper, we view the diffusion process as a continuous-time dynamical system, based …

abstract applications arxiv capability continuous cs.lg cs.si diffusion explore framework inference influence information network research scalable study traces type