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Spatio-temporal graph learning is a fundamental problem in modern urban systems.
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Graph Neural Processes for Spatio-Temporal Extrapolation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Spatio-temporal graph neural networks for predictive learning in urban computing: A survey
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PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation
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Diffstg: Probabilistic spatio-temporal graph forecasting with denoising diffusion models
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Automated Spatio-Temporal Graph Contrastive Learning. In Proceedings of the ACM Web Conference 2023 . 295–305
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INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging. In Proceedings of the ACM Web Conference 2023, WWW . 673–683
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SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting
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A survey on diffusion models for time series and spatio-temporal data
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