most citedResidual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks

15 citations · 15 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2021★ 15 cited

Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks

Huixuan Chi, Yuying Wang, Qinfen Hao +1

Graph Convolutional Networks (GCNs) and subsequent variants have been proposed to solve tasks on graphs, especially node classification tasks. In the literature, however, most tric…