729 citations · 807 across the 13 of their papers we have counts for
Showing 2023 · cs.LGShow all
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cs.LG2023
Robust Graph Structure Learning with the Alignment of Features and Adjacency Matrix
Shaogao Lv, Gang Wen, Shiyu Liu +2
To improve the robustness of graph neural networks (GNN), graph structure learning (GSL) has attracted great interest due to the pervasiveness of noise in graph data. Many approach…
cs.LG2023
Stability and Generalization of lp-Regularized Stochastic Learning for GCN
Shiyu Liu, Linsen Wei, Shaogao Lv +1
Graph convolutional networks (GCN) are viewed as one of the most popular representations among the variants of graph neural networks over graph data and have shown powerful perform…
cs.LG2023★ 2 cited
Permutation Equivariant Graph Framelets for Heterophilous Graph Learning
Jianfei Li, Ruigang Zheng, Han Feng +2
The nature of heterophilous graphs is significantly different from that of homophilous graphs, which causes difficulties in early graph neural network models and suggests aggregati…