STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction

ArXi:2508.12247v2 Announce Type: replace Recently, spatio-temporal time-series prediction has developed rapidly, yet existing deep learning methods struggle with learning complex long-term spatio-temporal dependencies efficiently. The long-term spatio-temporal dependency learning brings two new challenges: 1) The long-term temporal sequence naturally includes multiscale information, which is hard to extract efficiently; 2) The multiscale temporal information from different nodes is highly correlated and hard to model.