2026
Graph-Aware Diffusion for Signal Generation
ICASSP 2026poster
We study the problem of generating graph signals from unknown distributions defined over given graphs, relevant to domains such as recommender systems or sensor networks. Our approach builds on generative diffusion models, which are well established in vision and graph generation but remain underexp…