3 papers
cs.LG2026
Dimensional Balance Improves Large Scale Spatiotemporal Prediction Performance
Jing Chen, Shixiang Pan, Yujie Fan +3
Accurate spatiotemporal pattern analysis is critical in fields such as urban traffic, meteorology, and public health monitoring. However, existing methods face performance bottlene…
cs.LG2025
Dynamic Trend Fusion Module for Traffic Flow Prediction
Jing Chen, Haocheng Ye, Zhian Ying +2
Accurate traffic flow prediction is essential for applications like transport logistics but remains challenging due to complex spatio-temporal correlations and non-linear traffic p…
cs.LG2025
SFADNet: Spatio-temporal Fused Graph based on Attention Decoupling Network for Traffic Prediction
Mei Wu, Wenchao Weng, Jun Li +3
In recent years, traffic flow prediction has played a crucial role in the management of intelligent transportation systems. However, traditional prediction methods are often limite…