Heqing Huang

Pattern in Motion: Retrieval-Augmented Learning for Dynamic Spatio-Temporal Graphs.

Spatio-Temporal Graph Neural Networks (STGNNs) have emerged as powerful tools for modeling dynamic systems, yet they face critical generalization challenges in streaming Spatio-Temporal Out-of-Distribution (STOOD) scenarios, where spatial structures and temporal dynamics evolve beyond the distributions observed in hist...