Abstract: We investigate graph convolution networks with efficient learning from higher-order graph convolutions and direct learning from adjacency matrices for node classification. We revisit the ...

Abstract: Accurate short-term traffic flow forecasting is essential for intelligent transportation systems (ITS) and urban operations. However, most graph neural network (GNN) approaches rely on ...

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