3 papers
cs.LG2025
Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood
Gilhyun Nam, Taewon Kim, Joonhyun Jeong +1
Test-time adaptation (TTA) enables efficient adaptation of deployed models, yet it often leads to poorly calibrated predictive uncertainty - a critical issue in high-stakes domains…
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…
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…