39 citations · 55 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Building Shortcuts between Distant Nodes with Biaffine Mapping for Graph Convolutional Networks
Acong Zhang, Jincheng Huang, Ping Li +1
Multiple recent studies show a paradox in graph convolutional networks (GCNs), that is, shallow architectures limit the capability of learning information from high-order neighbors…
cs.LG2023★ 39 cited
Robust Mid-Pass Filtering Graph Convolutional Networks
Jincheng Huang, Lun Du, Xu Chen +3
Graph convolutional networks (GCNs) are currently the most promising paradigm for dealing with graph-structure data, while recent studies have also shown that GCNs are vulnerable t…
cs.LG2022★ 15 cited
Revisiting the role of heterophily in graph representation learning: An edge classification perspective
Jincheng Huang, Ping Li, Rui Huang +2
Graph representation learning aim at integrating node contents with graph structure to learn nodes/graph representations. Nevertheless, it is found that many existing graph learnin…