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SOUP: Spatial-Temporal Demand Forecasting and Competitive Supply
We consider a setting with an evolving set of requests for transportatio...
09/24/2020 ∙ by Bolong Zheng, et al. ∙
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Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes
Graph convolutional neural networks (GCNs) have recently demonstrated pr...
02/26/2020 ∙ by Jilin Hu, et al. ∙
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Recurrent Multi-Graph Neural Networks for Travel Cost Prediction
Origin-destination (OD) matrices are often used in urban planning, where...
11/13/2018 ∙ by Jilin Hu, et al. ∙
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Learning to Route with Sparse Trajectory Sets---Extended Version
Motivated by the increasing availability of vehicle trajectory data, we ...
02/22/2018 ∙ by Chenjuan Guo, et al. ∙
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