2 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
Riemannian Denoising Model for Molecular Structure Optimization with Chemical Accuracy
Jeheon Woo, Seonghwan Kim, Jun Hyeong Kim +1
We introduce a framework for molecular structure optimization using denoising model on a physics-informed Riemannian manifold (R-DM). Unlike conventional approaches operating in Eu…
Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon +3
Transporting between arbitrary distributions is a fundamental goal in generative modeling. Recently proposed diffusion bridge models provide a potential solution, but they rely on…
Transition Path Sampling with Improved Off-Policy Training of Diffusion Path Samplers
Kiyoung Seong, Seonghyun Park, Seonghwan Kim +2
Understanding transition pathways between two meta-stable states of a molecular system is crucial to advance drug discovery and material design. However, unbiased molecular dynamic…