3 papers
cs.LG2025
Learning Flexible Forward Trajectories for Masked Molecular Diffusion
Hyunjin Seo, Taewon Kim, Sihyun Yu +1
Masked diffusion models (MDMs) have achieved notable progress in modeling discrete data, while their potential in molecular generation remains underexplored. In this work, we explo…
cs.LG2024
Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with Topology-grouping Strategy
Hyunjin Seo, Kyusung Seo, Joonhyung Park +1
Recent advancements in graph neural networks (GNNs) have highlighted the critical need of calibrating model predictions, with neighborhood prediction similarity recognized as a piv…
physics.chem-ph2024
REBIND: Enhancing ground-state molecular conformation via force-based graph rewiring
Taewon Kim, Hyunjin Seo, Sungsoo Ahn +1
Predicting the ground-state 3D molecular conformations from 2D molecular graphs is critical in computational chemistry due to its profound impact on molecular properties. Deep lear…