4 papers · 1 filter
Converse and Collision-Based Achievability for Node Localization with Hybrid Distance-Spectral Graph Positional Encodings
Zimo Yan, Yifan Li, Hao Li +4
Graph positional encodings are widely used in graph neural networks and graph Transformers, yet it remains unclear when the code itself can identify nodes. We study a hybrid distan…
Resolving Node Identifiability in Graph Neural Processes via Laplacian Spectral Encodings
Zimo Yan, Zheng Xie, Chang Liu +1
Message passing graph neural networks are widely used for learning on graphs, yet their expressive power is limited by the one-dimensional Weisfeiler-Lehman test and can fail to di…
A Multi-Scale Graph Neural Process with Cross-Drug Co-Attention for Drug-Drug Interactions Prediction
Zimo Yan, Jie Zhang, Zheng Xie +2
Accurate prediction of drug-drug interactions (DDI) is crucial for medication safety and effective drug development. However, existing methods often struggle to capture structural…
MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design
Zimo Yan, Jie Zhang, Zheng Xie +3
Molecular generation plays an important role in drug discovery and materials science, especially in data-scarce scenarios where traditional generative models often struggle to achi…