Funder
National Natural Science Foundation of China
Subject
Artificial Intelligence,Cognitive Neuroscience
Reference37 articles.
1. Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction;Ali;Neural Networks,2022
2. IGAGCN: Information geometry and attention-based spatiotemporal graph convolutional networks for traffic flow prediction;An;Neural Networks,2021
3. DGInet: Dynamic graph and interaction-aware convolutional network for vehicle trajectory prediction;An;Neural Networks,2022
4. Adaptive graph convolutional recurrent network for traffic forecasting;Bai,2020
5. Bai, S., Kolter, J.Z., & Koltun, V. (2018). An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271.
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