2 papers
physics.soc-ph2021
Modeling Spatial Nonstationarity via Deformable Convolutions for Deep Traffic Flow Prediction
Wei Zeng, Chengqiao Lin, Kang Liu +2
Deep neural networks are being increasingly used for short-term traffic flow prediction, which can be generally categorized as convolutional (CNNs) or graph neural networks (GNNs).…
cs.CV2020
Revisiting the Modifiable Areal Unit Problem in Deep Traffic Prediction with Visual Analytics
Wei Zeng, Chengqiao Lin, Juncong Lin +4
Deep learning methods are being increasingly used for urban traffic prediction where spatiotemporal traffic data is aggregated into sequentially organized matrices that are then fe…