An Input-Conditioned Dynamic Hierarchical Spatiotemporal Graph Convolutional Network for Traffic Flow Prediction
Overall, DH-STGCN provides a flexible input-conditioned hierarchical representation for multistep traffic flow prediction, and Controlled hierarchy comparisons favor the window-conditioned assignment over fixed-uniform, static-hard, globally shared, and alternative differentiable assignments.