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Traditional methods for demand forecasting only focus on modeling the temporal dependency.
From Community to Role-based Graph Embeddings
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Semi-Supervised Classification with Graph Convolutional Networks
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Time-series extreme event forecasting with neural networks at uber
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Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting
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ST-CNN: Spatial-Temporal Convolutional Neural Network for crowd counting in videos
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Graph WaveNet for Deep Spatial-Temporal Graph Modeling
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Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting
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