3 papers
cs.LG2025
Rethinking Federated Graph Learning: A Data Condensation Perspective
Hao Zhang, Xunkai Li, Yinlin Zhu +1
Federated graph learning is a widely recognized technique that promotes collaborative training of graph neural networks (GNNs) by multi-client graphs.However, existing approaches h…
cs.LG2024
Empirical Evidence for the Fragment level Understanding on Drug Molecular Structure of LLMs
Xiuyuan Hu, Guoqing Liu, Yang Zhao +1
AI for drug discovery has been a research hotspot in recent years, and SMILES-based language models has been increasingly applied in drug molecular design. However, no work has exp…
cs.LG2022
Coordinating Cross-modal Distillation for Molecular Property Prediction
Hao Zhang, Nan Zhang, Ruixin Zhang +3
In recent years, molecular graph representation learning (GRL) has drawn much more attention in molecular property prediction (MPP) problems. The existing graph methods have demons…