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Modeling multivariate time series has long been a subject that has attracted researchers from a diverse range of fields including economics, finance, and traffic.
Time series forecasting using a hybrid ARIMA and neural network model
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MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. In Proc. of ICML
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Spatial temporal graph convolutional networks for skeleton-based action recognition. In Proc. of AAAI . 3482–3489
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Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting. In Proc. of IJCAI . 3634–3640
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Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. In Proc. of KDD
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DAGCN: Dual Attention Graph Convolutional Networks. In Proc. of IJCNN
Fengwen Chen, Shirui Pan, Jing Jiang, Huan Huo, and Guodong Long. 2019b
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Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting. In Proc. of AAAI
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Temporal pattern attention for multivariate time series forecasting
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Graph WaveNet for Deep Spatial-Temporal Graph Modeling. In Proc. of IJCAI
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GMAN: A Graph Multi-Attention Network for Traffic Prediction. In Proc. of AAAI
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