74 citations · 178 across the 9 of their papers we have counts for
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cs.LG2020★ 1 cited
Rethinking Graph Regularization for Graph Neural Networks
Han Yang, Kaili Ma, James Cheng
The graph Laplacian regularization term is usually used in semi-supervised representation learning to provide graph structure information for a model . However, with the rece…
cs.LG2020★ 12 cited
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives
Guoji Fu, Yifan Hou, Jian Zhang +3
Graph neural networks (GNNs) have attracted much attention because of their excellent performance on tasks such as node classification. However, there is inadequate understanding o…