Structure-Guided GNN combines the original graph with k-NN graphs built from role and global structural attributes and learns per-graph weights, achieving top results on 10 of 11 node-classification datasets.
A survey of convolutional neural networks: Analysis, applications, and prospects,
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Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery
Structure-Guided GNN combines the original graph with k-NN graphs built from role and global structural attributes and learns per-graph weights, achieving top results on 10 of 11 node-classification datasets.