2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks
Jiahua Rao, Jiancong Xie, Hanjing Lin +3
Graph Neural Networks (GNNs) have gained considerable traction for their capability to effectively process topological data, yet their interpretability remains a critical concern.…
cs.DB2023★ 2 cited
Node-based Knowledge Graph Contrastive Learning for Medical Relationship Prediction
Zhiguang Fan, Yuedong Yang, Mingyuan Xu +1
The embedding of Biomedical Knowledge Graphs (BKGs) generates robust representations, valuable for a variety of artificial intelligence applications, including predicting drug comb…