| FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting T Zhou, Z Ma, Q Wen, X Wang, L Sun, R Jin The 39th Int. Conf. on Machine Learning (ICML 2022), 2022 | 1777 | 2022 |
| Transformers in Time Series: A Survey Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun The 32nd Int. Joint Conf. on Artificial Intelligence (IJCAI 2023), 2023 | 1035 | 2023 |
| Time Series Data Augmentation for Deep Learning: A Survey Q Wen, L Sun, F Yang, X Song, J Gao, X Wang, H Xu The 30th Int. Joint Conf. on Artificial Intelligence (IJCAI 2021), 2021 | 936 | 2021 |
| 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, ... International Conference on Learning Representations (ICLR 2024), 2024 | 494 | 2024 |
| RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series Q Wen, J Gao, X Song, L Sun, H Xu, S Zhu The 33rd AAAI Conference on Artificial Intelligence (AAAI 2019) 33 (01 …, 2019 | 246 | 2019 |
| A survey on graph neural networks for time series: Forecasting, classification, imputation, and anomaly detection M Jin, HY Koh, Q Wen, D Zambon, C Alippi, GI Webb, I King, S Pan IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, 2024 | 203 | 2024 |
| RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks J Gao, X Song, Q Wen, P Wang, L Sun, H Xu ACM SIGKDD 2020 Workshop on Mining and Learning from Time Series (KDD 2020 WS), 2020 | 200 | 2020 |
| FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting T Zhou, Z Ma, X Wang, Q Wen, L Sun, T Yao, W Yin, R Jin 36th Conf. on Neural Information Processing Systems (NeurIPS 2022 Oral), 2022 | 199 | 2022 |
| DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection Y Yang, C Zhang, T Zhou, Q Wen, L Sun 29th ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2023), 2023 | 150 | 2023 |
| Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects K Zhang, Q Wen, C Zhang, R Cai, M Jin, Y Liu, J Zhang, Y Liang, G Pang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, 2024 | 145 | 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, ... arXiv preprint arXiv:2310.10196, 2023 | 126 | 2023 |
| 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 The 37th AAAI Conference on Artificial Intelligence (AAAI 2023), 2023 | 118 | 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 30th ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2024), 2024 | 115 | 2024 |
| A class of low complexity PTS techniques for PAPR reduction in OFDM systems Y Xiao, X Lei, Q Wen, S Li IEEE Signal Processing Letters (SPL 2007) 14 (10), 680-683, 2007 | 110 | 2007 |
| Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns Q Wen, Z Zhang, Y Li, L Sun ACM SIGKDD Conf. on Knowledge Discovery & Data Mining (KDD 2020), 2020 | 108 | 2020 |
| RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection Q Wen, K He, L Sun, Y Zhang, M Ke, H Xu ACM 2021 Int. Conf. on Management of Data (SIGMOD 2021), 2328-2337, 2021 | 90 | 2021 |
| Pathformer: Multi-scale transformers with Adaptive Pathways for Time Series Forecasting P Chen, Y Zhang, Y Cheng, Y Shu, Y Wang, Q Wen, B Yang, C Guo International Conference on Learning Representations (ICLR 2024), 2024 | 86* | 2024 |
| TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis C Zhang, T Zhou, Q Wen, L Sun 31st ACM Int. Conf. on Information & Knowledge Management (CIKM 2022), 2497-2507, 2022 | 83 | 2022 |
| Large language models for education: A survey and outlook S Wang, T Xu, H Li, C Zhang, J Liang, J Tang, PS Yu, Q Wen arXiv preprint arXiv:2403.18105, 2024 | 81 | 2024 |
| DiffSTG: Probabilistic spatio-temporal graph forecasting with denoising diffusion models H Wen, Y Lin, Y Xia, H Wan, Q Wen, R Zimmermann, Y Liang 31st Int. Conf. on Advances in Geographic Information Systems (SIGSPATIAL 2023), 2023 | 75 | 2023 |
Yuxuan LiangAssistant Professor, Hong Kong University of Science and Technology (Guangzhou)Verified email at hkust-gz.edu.cn
