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Asymmetric temporal dynamics and expanded receptive fields are unlocked in spatio-temporal graph forecasting by a unified spectral operator on cellular sheaves.
Ditch the global alignment: ST-Sheaf GNN learns dynamic, localized information flow for spatio-temporal forecasting, outperforming state-of-the-art methods by explicitly modeling latent local structure.