41 citations · 133 across the 8 of their papers we have counts for
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cs.LG2022★ 5 cited
Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) are popular machine learning methods for modeling graph data. A lot of GNNs perform well on homophily graphs while having unsatisfactory performance on…
cs.LG2022★ 21 cited
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) have shown expressive performance on graph representation learning by aggregating information from neighbors. Recently, some studies have discussed the…
cs.SI2022★ 3 cited
HTGN-BTW: Heterogeneous Temporal Graph Network with Bi-Time-Window Training Strategy for Temporal Link Prediction
Chongjian Yue, Lun Du, Qiang Fu +4
With the development of temporal networks such as E-commerce networks and social networks, the issue of temporal link prediction has attracted increasing attention in recent years.…