| Learning dynamics and heterogeneity of spatial-temporal graph data for traffic forecasting S Guo, Y Lin, H Wan, X Li, G Cong IEEE Transactions on Knowledge and Data Engineering 34 (11), 5415-5428, 2021 | 518 | 2021 |
| AirCloud: A cloud-based air-quality monitoring system for everyone Y Cheng, X Li, Z Li, S Jiang, Y Li, J Jia, X Jiang Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems …, 2014 | 339 | 2014 |
| Deep representation learning for trajectory similarity computation X Li, K Zhao, G Cong, CS Jensen, W Wei 2018 IEEE 34th international conference on data engineering (ICDE), 617-628, 2018 | 314 | 2018 |
| Learning travel time distributions with deep generative model X Li, G Cong, A Sun, Y Cheng The World Wide Web Conference, 1017-1027, 2019 | 88 | 2019 |
| Inf2vec: Latent representation model for social influence embedding S Feng, G Cong, A Khan, X Li, Y Liu, YM Chee 2018 IEEE 34th International Conference on Data Engineering (ICDE), 941-952, 2018 | 88 | 2018 |
| Robust road network representation learning: When traffic patterns meet traveling semantics Y Chen, X Li, G Cong, Z Bao, C Long, Y Liu, AK Chandran, R Ellison Proceedings of the 30th ACM International Conference on Information …, 2021 | 71 | 2021 |
| Spatial transition learning on road networks with deep probabilistic models X Li, G Cong, Y Cheng 2020 IEEE 36th International Conference on Data Engineering (ICDE), 349-360, 2020 | 44 | 2020 |
| Discovering pollution sources and propagation patterns in urban area X Li, Y Cheng, G Cong, L Chen Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 34 | 2017 |
| Multivariate time-series imputation with disentangled temporal representations S Liu, X Li, G Cong, Y Chen, Y Jiang The Eleventh international conference on learning representations, 2023 | 31 | 2023 |
| Fine-grained air quality monitoring based on gaussian process regression Y Cheng, X Li, Z Li, S Jiang, X Jiang Neural Information Processing: 21st International Conference, ICONIP 2014 …, 2014 | 28 | 2014 |
| Similar trajectory search with spatio-temporal deep representation learning DA Tedjopurnomo, X Li, Z Bao, G Cong, F Choudhury, AK Qin ACM Transactions on Intelligent Systems and Technology (TIST) 12 (6), 1-26, 2021 | 17 | 2021 |
| Points-of-interest relationship inference with spatial-enriched graph neural networks Y Chen, X Li, G Cong, C Long, Z Bao, S Liu, W Gu, F Zhang arXiv preprint arXiv:2202.13686, 2022 | 13 | 2022 |
| Biased temporal convolution graph network for time series forecasting with missing values X Chen, X Li, B Liu, Z Li The Twelfth International Conference on Learning Representations, 2023 | 8 | 2023 |
| Sinkhorn collaborative filtering X Li, JY Chin, Y Chen, G Cong Proceedings of the web conference 2021, 582-592, 2021 | 6 | 2021 |
| Finding dynamic co-evolving zones in spatial-temporal time series data Y Cheng, X Li, Y Li Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 6 | 2016 |
| Vector quantization pretraining for eeg time series with random projection and phase alignment H Gui, X Li, X Chen International Conference on Machine Learning, 16731-16750, 2024 | 3 | 2024 |
| DeepMeshCity: A Deep Learning Model for Urban Grid Prediction C Zhang, L Cai, M Chen, X Li, G Cong ACM Transactions on Knowledge Discovery from Data 18 (6), 1-26, 2024 | 3 | 2024 |
| SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting Y Jiang, X Li, Y Chen, S Liu, W Kong, AF Lentzakis, G Cong arXiv preprint arXiv:2406.12282, 2024 | 2 | 2024 |
| PGeoTopic: A Distributed Solution for Mining Geographical Topic Models K Zhao, G Cong, X Li IEEE Transactions on Knowledge and Data Engineering 34 (2), 881-893, 2020 | 2 | 2020 |
| Optimizing Smartphone App Usage Prediction: A Click-Through Rate Ranking Approach Y Zhang, M Kang, X Li, Y Qiu, Z Li Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 1 | 2024 |
Gao CongNanyang Technological University確認したメール アドレス: ntu.edu.sg