Xun Zhou

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

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

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

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

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

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

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

Zhang, Y. ., Li, Y. ., Zhou, X. ., Kong, X. ., & Luo, J. . (2022). STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation. In 2022 IEEE International Conference on Data Mining (ICDM) (p. 10). http://doi.org/10.1109/ICDM54844.2022.00085

Pan, M. ., Zhang, X. ., Li, Y. ., Zhou, X. ., & Luo, J. . (2021). Learning Decision Making Strategies of Non-experts: A NEXT-GAIL Model for Taxi Drivers. In SIGSPATIAL ’21: Proceedings of the 29th International Conference on Advances in Geographic Information Systems (p. 10). http://doi.org/10.1145/3474717.3483924

Zhang, X. ., Li, Y. ., Zhou, X. ., Mangoubi, O. ., Zhang, Z. ., Filardi, V. ., & Luo, J. . (2021). DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. In IEEE International Conference on Data Mining (ICDM). http://doi.org/10.1109/ICDM51629.2021.00102