The author introduces GRASP, a novel graph generative model based on spectral diffusion to efficiently generate graphs by leveraging the Laplacian spectrum. The approach aims to overcome computational bottlenecks and enhance expressivity in graph generative models.
Graph generation model GRASP utilizes spectral decomposition and diffusion to efficiently generate graphs while overcoming computational bottlenecks.