Wenqian Mu

Spatio-temporal Prototype-based Hierarchical Learning for OD Demand Prediction

Origin-Destination (OD) demand prediction is a pivotal yet highly challenging task in intelligent transportation systems, aiming to accurately forecast cross-region ridership flows within urban networks. While previous studies have focused on modeling node-to-node relationships, most of them neglect