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DiPhon: Diffusion on Graphons for Scalable Graph Generation
Sergio Rozada, Yiming Qin, Manuel Madeira +2
Diffusion models represent a leading paradigm for graph generation, with notable impact in domains such as molecular design. Yet, scaling these models to large graphs remains an op…
cs.LG2026
Balancing Symmetry and Efficiency in Graph Flow Matching
Benjamin Honoré, Alba Carballo-Castro, Yiming Qin +1
Equivariance is central to graph generative models, as it ensures the model respects the permutation symmetry of graphs. However, strict equivariance can increase computational cos…