Yueming Yin — accepted AI-conference papers

2026

Test-Time Adaptation without Source Data for Out-of-Domain Bioactivity Prediction

Yiming Yang, Zhiyuan Zhou, Yueming Yin, Hoi-Yeung Li, Adams Wai-Kin Kong

ICLR 2026poster

Accurate prediction of protein-ligand bioactivity is a cornerstone of modern drug discovery, yet current deep learning methods often struggle with out-of-domain (OOD) generalization. The existing methods rely on access to source data, making them impractical in scenarios where data cannot be accesse…

Cited by 0 Source ↗Scholar ↗

2025

Enhancing Bioactivity Prediction via Spatial Emptiness Representation of Protein-ligand Complex and Union of Multiple Pockets

Zhiyuan Zhou, Yueming Yin, Yiming Yang, Yuguang Mu, Hoi-Yeung Li, Adams Wai-Kin Kong

NeurIPS 2025poster

Predicting the bioactivity of candidate ligands remains a central challenge in drug discovery. Ligands and endogenous substrates often compete for the same binding sites on target proteins, and the extent to which a ligand can modulate protein function depends not only on its binding but also on how…

Cited by 0 Source ↗Scholar ↗