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Graph convolution network based approaches have been recently used to model region-wise relationships in region-level prediction problems in urban computing.
Transfer Knowledge between Cities
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How transferable are features in deep neural networks?
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DNN-based prediction model for spatio-temporal data
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
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Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
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Modeling Spatial-Temporal Dynamics for Traffic Prediction
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Hexagon-Based Convolutional Neural Network for Supply-Demand Forecasting of Ride-Sourcing Services
Ke, J.; Yang, H.; Zheng, H.; Chen, X.; Jia, Y.; Gong, P.; Ye, J · 2018
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Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
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Multi-task Representation Learning for Travel Time Estimation
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Learning multiple tasks with multilinear relationship networks
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Deep learning for precipitation nowcasting: A benchmark and a new model
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Multimodal machine learning: A survey and taxonomy
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