1.5k citations · 6.9k across the 102 of their papers we have counts for
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cs.LG2019★ 180 cited
Strategies for Pre-training Graph Neural Networks
Weihua Hu, Bowen Liu, Joseph Gomes +4
Many applications of machine learning require a model to make accurate pre-dictions on test examples that are distributionally different from training ones, while task-specific lab…
cs.LG2019★ 687 cited
GNNExplainer: Generating Explanations for Graph Neural Networks
Rex Ying, Dylan Bourgeois, Jiaxuan You +2
Graph Neural Networks (GNNs) are a powerful tool for machine learning on graphs.GNNs combine node feature information with the graph structure by recursively passing neural message…