| FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting T Zhou, Z Ma, Q Wen, X Wang, L Sun, R Jin Proceedings of the 39th International Conference on Machine Learning 162 …, 2022 | 1618 | 2022 |
| Transformers in time series: A survey Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun 2023 International Joint Conference on Artificial Intelligence(IJCAI 2023), 2022 | 952 | 2022 |
| One Fits All:power general time series analysis by pretrained lm T Zhou, PS Niu, X Wang, L Sun, R Jin 2023 Conference on Neural Information Processing Systems(Neurips 2023), 2023 | 335 | 2023 |
| FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting T Zhou, Z Ma, Q Wen, L Sun, T Yao, Y Wotao, R Jin 2022 Conference on Neural Information Processing Systems(Neurips 2022), 2022 | 187 | 2022 |
| DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection Y Yang, C Zhang, T Zhou, Q Wen, L Sun 29th SIGKDD Conference on Knowledge Discovery and Data Mining(KDD 2023), 2023 | 120 | 2023 |
| Dehydrogenation of n-Alkanes by Solid-Phase Molecular Pincer-Iridium Catalysts. High Yields of α-Olefin Product A Kumar, T Zhou, TJ Emge, O Mironov, RJ Saxton, K Krogh-Jespersen, ... Journal of the American Chemical Society 137 (31), 9894-9911, 2015 | 100 | 2015 |
| 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 |
| Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting L Chen, Weiqi and Wang, Wenwei and Peng, Bingqing and Wen, Qingsong and Zhou ... KDD '22, 146–156, 2022 | 68* | 2022 |
| Robust time series analysis and applications: An industrial perspective Q Wen, L Yang, T Zhou, L Sun Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 54 | 2022 |
| Sadi: A self-adaptive decomposed interpretable framework for electric load forecasting under extreme events H Liu, Z Ma, L Yang, T Zhou, R Xia, Y Wang, Q Wen, L Sun ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 53 | 2023 |
| Catalytic Dehydrogenative C–C Coupling by a Pincer-Ligated Iridium Complex M Wilklow-Marnell, B Li, T Zhou, K Krogh-Jespersen, WW Brennessel, ... Journal of the American Chemical Society 139 (26), 8977-8989, 2017 | 43 | 2017 |
| Catalytic Alkane Transfer Dehydrogenation by PSP-Pincer-Ligated Ruthenium. Deactivation of an Extremely Reactive Fragment by Formation of Allyl Hydride Complexes X Zhou, S Malakar, T Zhou, S Murugesan, C Huang, TJ Emge, ... ACS Catalysis 9 (5), 4072-4083, 2019 | 41 | 2019 |
| Transformers in time series: A survey. arXiv Q Wen, T Zhou, C Zhang, W Chen, Z Ma, J Yan, L Sun arXiv preprint arXiv:2202.07125, 2022 | 37 | 2022 |
| CARD: Channel aligned robust blend transformer for time series forecasting X Wang, T Zhou, Q Wen, J Gao, B Ding, R Jin The Twelfth International Conference on Learning Representations, 2024 | 29 | 2024 |
| Single and Double C–H Activation of Biphenyl or Phenanthrene. An Example of C–H Addition to Ir (III) More Facile than Addition to Ir (I) DA Laviska, T Zhou, A Kumar, TJ Emge, K Krogh-Jespersen, AS Goldman Organometallics 35 (11), 1613-1623, 2016 | 21 | 2016 |
| GCformer: an efficient solution for accurate and scalable long-term multivariate time series forecasting Y Zhao, Z Ma, T Zhou, M Ye, L Sun, Y Qian Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 18 | 2023 |
| PNP-Pincer Complexes of Osmium: Comparison with Isoelectronic (PCP)Ir and (PNP)Ir+ Units N Lease, EM Pelczar, T Zhou, S Malakar, TJ Emge, F Hasanayn, ... Organometallics 37 (3), 314-326, 2018 | 17 | 2018 |
| Energy forecasting with robust, flexible, and explainable machine learning algorithms Z Zhu, W Chen, R Xia, T Zhou, P Niu, B Peng, W Wang, H Liu, Z Ma, X Gu, ... AI Magazine 44 (4), 377-393, 2023 | 16 | 2023 |
| Transfer learning for the fully automatic segmentation of left ventricle myocardium in porcine cardiac cine MR images A Chen, T Zhou, I Icke, S Parimal, B Dogdas, J Forbes, S Sampath, ... Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018 | 16 | 2018 |
| Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning T Zhou, I Icke, B Dogdas, S Parimal, S Sampath, J Forbes, A Bagchi, ... Medical Imaging 2017: Image Processing 10133, 540-547, 2017 | 16 | 2017 |
Qingsong Wen (文青松)Head of AI & Chief Scientist @ Squirrel AIBestätigte E-Mail-Adresse bei gatech.edu