| Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting T Zhou, Z Ma, Q Wen, X Wang, L Sun, R Jin International conference on machine learning, 27268-27286, 2022 | 1646 | 2022 |
| Transformers in time series: A survey Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun arXiv preprint arXiv:2202.07125, 2022 | 961 | 2022 |
| Time series data augmentation for deep learning: A survey Q Wen, L Sun, F Yang, X Song, J Gao, X Wang, H Xu arXiv preprint arXiv:2002.12478, 2020 | 919 | 2020 |
| Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation S Huang, J Li, L Sun, J Ye, A Fleisher, T Wu, K Chen, E Reiman, ... NeuroImage 50 (3), 935-949, 2010 | 369 | 2010 |
| One fits all: Power general time series analysis by pretrained lm T Zhou, P Niu, L Sun, R Jin Advances in neural information processing systems 36, 43322-43355, 2023 | 343 | 2023 |
| Canonical correlation analysis for multilabel classification: A least-squares formulation, extensions, and analysis L Sun, S Ji, J Ye IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (1), 194-200, 2010 | 338 | 2010 |
| Hypergraph spectral learning for multi-label classification L Sun, S Ji, J Ye Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 296 | 2008 |
| RobustSTL: A robust seasonal-trend decomposition algorithm for long time series Q Wen, J Gao, X Song, L Sun, H Xu, S Zhu Proceedings of the AAAI conference on artificial intelligence 33 (01), 5409-5416, 2019 | 242 | 2019 |
| Robusttad: Robust time series anomaly detection via decomposition and convolutional neural networks J Gao, X Song, Q Wen, P Wang, L Sun, H Xu arXiv preprint arXiv:2002.09545, 2020 | 199 | 2020 |
| Film: Frequency improved legendre memory model for long-term time series forecasting T Zhou, Z Ma, Q Wen, L Sun, T Yao, W Yin, R Jin Advances in neural information processing systems 35, 12677-12690, 2022 | 191 | 2022 |
| Dcdetector: Dual attention contrastive representation learning for time series anomaly detection Y Yang, C Zhang, T Zhou, Q Wen, L Sun Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 124 | 2023 |
| Fast RobustSTL: Efficient and robust seasonal-trend decomposition for time series with complex patterns Q Wen, Z Zhang, Y Li, L Sun Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 108 | 2020 |
| A least squares formulation for canonical correlation analysis L Sun, S Ji, J Ye Proceedings of the 25th international conference on Machine learning, 1024-1031, 2008 | 97 | 2008 |
| On the equivalence between canonical correlation analysis and orthonormalized partial least squares L Sun, S Ji, S Yu, J Ye Twenty-First International Joint Conference on Artificial Intelligence, 2009 | 96 | 2009 |
| Learning brain connectivity of Alzheimer's disease from neuroimaging data S Huang, J Li, L Sun, J Liu, T Wu, K Chen, A Fleisher, E Reiman, J Ye Advances in Neural Information Processing Systems 22, 2009 | 93 | 2009 |
| Multi-label dimensionality reduction L Sun, S Ji, J Ye CRC Press, 2013 | 92 | 2013 |
| RobustPeriod: Robust time-frequency mining for multiple periodicity detection Q Wen, K He, L Sun, Y Zhang, M Ke, H Xu Proceedings of the 2021 international conference on management of data, 2328 …, 2021 | 89 | 2021 |
| Efficient recovery of jointly sparse vectors L Sun, J Liu, J Chen, J Ye Advances in Neural Information Processing Systems 22, 2009 | 89 | 2009 |
| TFAD: A decomposition time series anomaly detection architecture with time-frequency analysis C Zhang, T Zhou, Q Wen, L Sun Proceedings of the 31st ACM International Conference on Information …, 2022 | 80 | 2022 |
| Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation L Sun, R Patel, J Liu, K Chen, T Wu, J Li, E Reiman, J Ye Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 70 | 2009 |
Qingsong Wen (文青松)Head of AI & Chief Scientist @ Squirrel AIZweryfikowany adres z gatech.edu