Abstract: Traffic flow prediction is fundamental to intelligent transportation systems, requiring accurate modeling of complex spatio-temporal dependencies. Existing methods typically assume ...
Abstract: Graph neural networks (GNNs) have demonstrated significant advantages in handling data from non-Euclidean domains. Given the successful application of neural architecture search (NAS) in ...
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