| Time-llm: Time series forecasting by reprogramming large language models M Jin, S Wang, L Ma, Z Chu, JY Zhang, X Shi, PY Chen, Y Liang, YF Li, ... ICLR 2024, 2024 | 1243 | 2024 |
| Urban traffic prediction from spatio-temporal data using deep meta learning Z Pan, Y Liang, W Wang, Y Yu, Y Zheng, J Zhang KDD 2019, 2019 | 708 | 2019 |
| Geoman: Multi-level attention networks for geo-sensory time series prediction. Y Liang, S Ke, J Zhang, X Yi, Y Zheng IJCAI 2018, 2018 | 669 | 2018 |
| Spatio-temporal graph neural networks for predictive learning in urban computing: A survey G Jin, Y Liang*, Y Fang, Z Shao, J Huang, J Zhang, Y Zheng IEEE TKDE 2023, 2023 | 539 | 2023 |
| Foundation models for time series analysis: A tutorial and survey Y Liang, H Wen, Y Nie, Y Jiang, M Jin, D Song, S Pan, Q Wen KDD 2024, 2024 | 399 | 2024 |
| Self-supervised learning for time series analysis: Taxonomy, progress, and prospects K Zhang, Q Wen, C Zhang, R Cai, M Jin, Y Liu, JY Zhang, Y Liang, ... IEEE TPAMI 2024, 2024 | 329 | 2024 |
| Mixup for node and graph classification Y Wang, W Wang, Y Liang, Y Cai, B Hooi WWW 2021, 2021 | 266 | 2021 |
| Predicting citywide crowd flows in irregular regions using multi-view graph convolutional networks J Sun, J Zhang, Q Li, X Yi, Y Liang, Y Zheng IEEE TKDE 2020, 2020 | 265 | 2020 |
| Urban water quality prediction based on multi-task multi-view learning Y Liu, Y Zheng, Y Liang, S Liu, DS Rosenblum IJCAI 2016, 2016 | 246 | 2016 |
| Federated forest Y Liu, Y Liu, Z Liu, Y Liang, C Meng, J Zhang, Y Zheng IEEE TBD 2020, 2020 | 238 | 2020 |
| Msgnet: Learning multi-scale inter-series correlations for multivariate time series forecasting W Cai, Y Liang, X Liu, J Feng, Y Wu AAAI 2024, 2024 | 237 | 2024 |
| Large models for time series and spatio-temporal data: A survey and outlook M Jin, Q Wen, Y Liang, C Zhang, S Xue, X Wang, J Zhang, Y Wang, ... Preprint - Survey Paper, 2023 | 219 | 2023 |
| Largest: A benchmark dataset for large-scale traffic forecasting X Liu, Y Xia, Y Liang*, J Hu, Y Wang, L Bai, C Huang, Z Liu, B Hooi, ... NeurIPS 2023, 2023 | 206 | 2023 |
| Unitime: A language-empowered unified model for cross-domain time series forecasting X Liu, J Hu, Y Li, S Diao, Y Liang*, B Hooi, R Zimmermann WWW 2024, 2024 | 205 | 2024 |
| Airformer: Predicting nationwide air quality in china with transformers Y Liang, Y Xia, S Ke, Y Wang, Q Wen, J Zhang, Y Zheng, R Zimmermann AAAI 2023, 2023 | 204 | 2023 |
| Nodeaug: Semi-supervised node classification with data augmentation Y Wang, W Wang, Y Liang, Y Cai, J Liu, B Hooi KDD 2020, 2020 | 196 | 2020 |
| Multi-behavior hypergraph-enhanced transformer for sequential recommendation Y Yang, C Huang, L Xia, Y Liang, Y Yu, C Li KDD 2022, 2022 | 195 | 2022 |
| Directed graph convolutional network Z Tong, Y Liang, C Sun, DS Rosenblum, A Lim Preprint, 2020 | 179 | 2020 |
| Spatio-temporal meta learning for urban traffic prediction Z Pan, W Zhang, Y Liang, W Zhang, Y Yu, J Zhang, Y Zheng IEEE TKDE 2020, 2020 | 176 | 2020 |
| Position: What can large language models tell us about time series analysis M Jin, Y Zhang, W Chen, K Zhang, Y Liang*, B Yang, J Wang, S Pan*, ... ICML 2024 Position Paper, 2024 | 169* | 2024 |
Qingsong Wen (文青松)Head of AI @ Squirrel Ai Learning, PhD Supervisor @ University of OxfordVerified email at gatech.edu
