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News/Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models
arxiv
PublishedJune 4, 2026 at 4:00 AM
—neutral

Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models

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arXiv:2606.04672v1 Announce Type: cross Abstract: Continuous-time dynamic graphs (CTDGs) provide a richer framework to capture fine-grained temporal patterns in evolving relational data. Long-range information propagation is a key challenge while learning representations, wherein it is important to

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