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A Supplementary Material

Neural Information Processing Systems

In the supplementary material, we provide additional information and details in A.1. This section covers the introduction of data, key parameter settings, comparisons with baselines, optimization methods, and the algorithm process of our method. The statistical information of the aforementioned four real-world datasets is presented in Table 4. These datasets primarily consist of daily spatio-temporal statistics in the United States. We perform 2 dynamic routing iterations.




GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks

Neural Information Processing Systems

While advanced end-to-end models have achieved notable success in improving predictive performance, their integration and expansion pose significant challenges.