Yanhua Li

Zhang, Y. ., Li, Y. ., Zhou, X. ., Luo, J. ., & Zhang, Z.-L. . (2022). Urban Traffic Dynamics Prediction—A Continuous Spatial-temporal Meta-learning Approach. ACM Transactions on Intelligent Systems and Technology, 13(2), 19. http://doi.org/10.1145/3474837

An, B. ., Vahedian, A. ., Zhou, X. ., Street, N. W., & Li, Y. . (2022). HintNet: Hierarchical Knowledge Transfer Networks for Traffic Accident Forecasting on Heterogeneous Spatio-Temporal Data. In 2022 SIAM International Conference on Data Mining (SDM). http://doi.org/10.1137/1.9781611977172.38

Zhang, Y. ., Li, Y. ., Zhou, X. ., & Luo, J. . (2022). Mest-GAN: Cross-City Urban Traffic Estimation with Meta Spatial-Temporal Generative Adversarial Networks. In 2022 IEEE International Conference on Data Mining (ICDM) (p. 10). http://doi.org/10.1109/ICDM54844.2022.00084

Ding, Y. ., Zhang, Z. ., Li, Y. ., & Zhou, X. . (2022). EgoSpeed-net: forecasting speed-control in driver behavior from egocentric video data. In SIGSPATIAL ’22: Proceedings of the 30th International Conference on Advances in Geographic Information Systems (p. 10). http://doi.org/10.1145/3557915.3560946

Bao, H. ., Zhou, X. ., Xie, Y. ., Li, Y. ., & Jia, X. . (2022). STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19. In 2022 IEEE International Conference on Data Mining (ICDM) (p. 10). http://doi.org/10.1109/ICDM54844.2022.00010

Zhang, X. ., Li, Y. ., Zhang, Z. ., & Zhang, Z.-L. . (2023). Domain Disentangled Meta-Learning. In 2023 SIAM International Conference on Data Mining (SDM). http://doi.org/10.1137/1.9781611977653.ch61

Zhang, Y. ., Li, Y. ., Zhou, X. ., Zhang, Z. ., & Luo, J. . (2023). STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies. In 2023 SIAM International Conference on Data Mining (SDM). http://doi.org/10.1137/1.9781611977653.ch24

Hu, M. ., Zhang, X. ., Li, Y. ., Zhou, X. ., & Luo, J. . (2023). ST-iFGSM: Enhancing Robustness of Human Mobility Signature Identification Model via Spatial-Temporal Iterative FGSM. In the 29th SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2023). Retrieved from https://par.nsf.gov/biblio/10420177

Xie, Y. ., Wang, Z. ., Mai, G. ., Li, Y. ., Jia, X. ., Gao, S. ., & Wang, S. . (2023). Geo-Foundation Models: Reality, Gaps and Opportunities. In (p. 4). ACM. http://doi.org/10.1145/3589132.3625616

Busaranuvong, P. ., Zhang, X. ., Li, Y. ., Zhou, X. ., & Luo, J. . (2023). CAC: Enabling Customer-Centered Passenger-Seeking for Self-Driving Ride Service with Conservative Actor-Critic. In (p. 10). IEEE. http://doi.org/10.1109/ICDM58522.2023.00011