9 citations · 9 across the 1 of their papers we have counts for
3 papers
cs.LG2026★ 9 cited
Riemannian Denoising Diffusion Probabilistic Models
Zichen Liu, Wei Zhang, Christof Schütte +1
We propose Riemannian Denoising Diffusion Probabilistic Models (RDDPMs) for learning distributions on submanifolds of Euclidean space that are level sets of functions, including mo…
cs.LG2026
FES-FM: Free Energy Surface Sampling via Reduced Flow Matching
Zichen Liu, Tiejun Li
Sampling the distribution of collective variables (CVs) and estimating the associated free energy surface are crucial problems in statistical physics, as they underpin a better und…
cs.LG2026
Improving the Euclidean Diffusion Generation of Manifold Data by Mitigating Score Function Singularity
Zichen Liu, Wei Zhang, Tiejun Li
Euclidean diffusion models have achieved remarkable success in generative modeling across diverse domains, and they have been extended to manifold cases in recent advances. Instead…