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

Ayushman Raghuvanshi, Thummaluru Siddartha Reddy, Sundeep Prabhakar Chepuri, Mahesh Chandran

Jun 5, 2026 at 04:00

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arXiv:2606.04672v2 Announce Type: replace-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 retain and update information over long...

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