Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting
Author:
Affiliation:
1. Peking University,School of Computer Science
2. University of California Los Angeles,Department of Computer Science
3. Terminus Group
Funder
Research and Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10184508/10184509/10184800.pdf?arnumber=10184800
Reference66 articles.
1. Diffusion convolutional recurrent neural network: Data-driven traffic forecasting;li;Proceedings of the International Conference on Learning Representations,2018
2. Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
3. Semi-supervised classification with graph convolutional networks;kipf;ArXiv,2016
4. DSANet
5. GMAN: A Graph Multi-Attention Network for Traffic Prediction
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