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cs.LG2026
Riemannian Diffusion Models on General Manifolds via Physics-Informed Neural Networks
Gyeonghoon Ko, Juho Lee
Riemannian diffusion models generalize score-based generative modeling to manifold-supported data via stochastic diffusion equations on the manifold. However, training requires sam…
cs.LG2026
Permutation-Symmetrized Diffusion for Unconditional Molecular Generation
Gyeonghoon Ko, Juho Lee
Permutation invariance is fundamental in molecular point-cloud generation, yet most diffusion models enforce it indirectly via permutation-equivariant networks on an ordered space.…