AI RESEARCH
CROSS-Net: Region-Agnostic Taxi-Demand Prediction Using Feature Disentanglement
arXiv CS.LG
•
ArXi:2310.18215v2 Announce Type: replace The growing demand for ride-hailing services has led to an increasing need for accurate taxi demand prediction. Existing systems are limited to specific regions, lacking generality to unseen areas. This paper presents a novel taxi demand prediction system, harnessing the strengths of multiview graph neural networks to capture spatial-temporal dependencies and patterns in urban environments.