3 papers
cs.LG2026
Geometry-Informed Parameter-Efficient Fine-Tuning of Pre-trained Molecular GNNs for Blood-Brain Barrier Permeability Prediction
Marco Vieto Vega, Long D. Nguyen, Binh P. Nguyen
Blood-brain barrier permeability (BBBP) prediction is a critical screening task in central nervous system drug discovery, where candidate molecules must be assessed for whether the…
cs.LG2026
MAGPrompt: Message-Adaptive Graph Prompt Tuning for Graph Neural Networks
Long D. Nguyen, Binh P. Nguyen
Pre-trained graph neural networks (GNNs) transfer well, but adapting them to downstream tasks remains challenging due to mismatches between pre-training objectives and task require…
cs.LG2026
Topology-Aware Multiscale Mixture of Experts for Efficient Molecular Property Prediction
Long D. Nguyen, Kelin Xia, Binh P. Nguyen
Many molecular properties depend on 3D geometry, where non-covalent interactions, stereochemical effects, and medium- to long-range forces are determined by spatial distances and a…