A supervised edge-sampling sparsifier that keeps only 20% of edges can match or beat the full graph for GNN node classification, with especially large gains on heterophilic graphs.
Cluster- GCN : An efficient algorithm for training deep and large graph convolutional networks
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SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks
A supervised edge-sampling sparsifier that keeps only 20% of edges can match or beat the full graph for GNN node classification, with especially large gains on heterophilic graphs.