5 citations · 5 across the 5 of their papers we have counts for
4 papers · 1 filter
Self-Attention Empowered Graph Convolutional Network for Structure Learning and Node Embedding
Mengying Jiang, Guizhong Liu, Yuanchao Su +1
In representation learning on graph-structured data, many popular graph neural networks (GNNs) fail to capture long-range dependencies, leading to performance degradation. Furtherm…
Hierarchical Multi-Relational Graph Representation Learning for Large-Scale Prediction of Drug-Drug Interactions
Mengying Jiang, Guizhong Liu, Yuanchao Su +2
Most existing methods for predicting drug-drug interactions (DDI) predominantly concentrate on capturing the explicit relationships among drugs, overlooking the valuable implicit c…
Relation-aware graph structure embedding with co-contrastive learning for drug-drug interaction prediction
Mengying Jiang, Guizhong Liu, Biao Zhao +2
Relation-aware graph structure embedding is promising for predicting multi-relational drug-drug interactions (DDIs). Typically, most existing methods begin by constructing a multi-…
GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily
Mengying Jiang, Guizhong Liu, Yuanchao Su +1
In representation learning on the graph-structured data, under heterophily (or low homophily), many popular GNNs may fail to capture long-range dependencies, which leads to their p…