Yanhua Li

Ding, Y. ., Zhou, X. ., Bao, H. ., Li, Y. ., Hamann, C. ., Spears, S. ., & Yuan, Z. . (2020). Cycling-Net: A Deep Learning Approach to Predicting Cyclist Behaviors from Geo-Referenced Egocentric Video Data. In Proceedings of the 28th International Conference on Advances in Geographic Information Systems (p. 10). http://doi.org/10.1145/3397536.3422258

Zhang, Y. ., Li, Y. ., Zhou, X. ., & Luo, J. . (2020). cST-ML: Continuous Spatial-Temporal Meta-Learning for Traffic Dynamics Prediction. In 2020 IEEE International Conference on Data Mining (ICDM) (p. 6). http://doi.org/10.1109/icdm50108.2020.00187

Zhang, X. ., Li, Y. ., Zhou, X. ., Zhang, Z. ., & Luo, J. . (2020). TrajGAIL: Trajectory Generative Adversarial Imitation Learning for Long-Term Decision Analysis. In 2020 IEEE International Conference on Data Mining (ICDM) (p. 10). http://doi.org/10.1109/ICDM50108.2020.00089

Pan, M. ., Huang, W. ., Li, Y. ., Zhou, X. ., & Luo, J. . (2020). xGAIL: Explainable Generative Adversarial Imitation Learning for Explainable Human Decision Analysis. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (p. 10). http://doi.org/10.1145/3394486.3403186

Zhang, Y. ., Li, Y. ., Zhou, X. ., Kong, X. ., & Luo, J. . (2020). Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (p. 11). http://doi.org/10.1145/3394486.3403127

Ren, H. ., Pan, M. ., Li, Y. ., Zhou, X. ., & Luo, J. . (2020). ST-SiameseNet: Spatio-Temporal Siamese Networks for Human Mobility Signature Identification. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (p. 10). http://doi.org/10.1145/3394486.3403183

Yang, M. ., Li, Y. ., Zhou, X. ., Lu, H. ., Tian, Z. ., & Luo, J. . (2020). Inferring Passengers’ Interactive Choices on Public Transits via MA-AL: Multi-Agent Apprenticeship Learning. In The Web Conference 2020 (p. 11). http://doi.org/10.1145/3366423.3380235

He, T. ., Bao, J. ., Li, R. ., Ruan, S. ., Li, Y. ., Song, L. ., … Zheng, Y. . (2020). What is the Human Mobility in a New City: Transfer Mobility Knowledge Across Cities. In The Web Conference 2020 (p. 11). http://doi.org/10.1145/3366423.3380210

Ruan, S. ., Bao, J. ., Liang, Y. ., Li, R. ., He, T. ., Meng, C. ., … Zheng, Y. . (2020). Dynamic Public Resource Allocation Based on Human Mobility Prediction. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(1), 22. http://doi.org/10.1145/3380986

Ye, W. ., Hu, X. ., Liu, T. ., Sun, R. ., Li, Y. ., & Zhang, Z.-L. . (2022). 5GNN: extrapolating 5G measurements through GNNs. In Proceedings of the 1st International Workshop on Graph Neural Networking (GNNet ’22: ) (p. 6). http://doi.org/10.1145/3565473.3569186