EdgeGFL multiplies node messages by learned edge-type vectors to implement per-dimension feature preference in heterogeneous graph neural networks, reporting small gains over prior GNN baselines.
Multi-hierarchical spatial- temporal graph convolutional networks for traffic flow forecasting,
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EdgeGFL: Rethinking Edge Information in Graph Feature Preference Learning
EdgeGFL multiplies node messages by learned edge-type vectors to implement per-dimension feature preference in heterogeneous graph neural networks, reporting small gains over prior GNN baselines.