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Addressing Spatial Indistinguishability in Spatiotemporal Prediction via Optimal Transport-Guided Masking
Spatiotemporal prediction aims to learn discriminative representations from correlated temporal signals over spatial structures for accurate future inference. A central challenge is \emph{spatial indistinguishability}: different nodes may share similar historical patterns yet evolve toward divergent
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