Funder
Shenzhen Science and Technology Innovation Commission
Wuhan Science and Technology Bureau
Reference36 articles.
1. Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction;Ali;Neural Networks,2022
2. DGInet: Dynamic graph and interaction-aware convolutional network for vehicle trajectory prediction;An;Neural Networks,2022
3. Bengio, Y., Louradour, J., Collobert, R., & Weston, J. (2009). Curriculum Learning. In Proceedings of the 26th annual international conference on machine learning (pp. 41–48).
4. Adversarial contrastive estimation;Bose,2018
5. Learning and development in neural networks: The importance of starting small;Elman;Cognition,1993