| Mts-mixers: Multivariate time series forecasting via factorized temporal and channel mixing Z Li, Z Rao, L Pan, Z Xu arXiv preprint arXiv:2302.04501, 2023 | 92 | 2023 |
| Ti-mae: Self-supervised masked time series autoencoders Z Li, Z Rao, L Pan, P Wang, Z Xu arXiv preprint arXiv:2301.08871, 2023 | 48 | 2023 |
| Rose: Register assisted general time series forecasting with decomposed frequency learning Y Wang, Y Qiu, P Chen, K Zhao, Y Shu, Z Rao, L Pan, B Yang, C Guo arXiv preprint arXiv:2405.17478, 2024 | 5 | 2024 |
| SMARTformer: Semi-Autoregressive Transformer with Efficient Integrated Window Attention for Long Time Series Forecasting. Y Li, S Qi, Z Li, Z Rao, L Pan, Z Xu IJCAI, 2169-2177, 2023 | 5 | 2023 |
| Enhancing multivariate time series forecasting with mutual information-driven cross-variable and temporal modeling S Qi, L Wen, Y Li, Y Yang, Z Li, Z Rao, L Pan, Z Xu arXiv preprint arXiv:2403.00869, 2024 | 2 | 2024 |
| Wind Power Forecasting with Deep Learning: Team didadida_hualahuala M Kalander, Z Rao, C Zhang KDD 2022, 2022 | 2 | 2022 |
| Air quality prediction with physics-informed dual neural odes in open systems J Tian, Y Liang, R Xu, P Chen, C Guo, A Zhou, L Pan, Z Rao, B Yang arXiv preprint arXiv:2410.19892, 2024 | 1 | 2024 |
| MTS-UNMixers: Multivariate Time Series Forecasting via Channel-Time Dual Unmixing X Zhu, D Shen, Z Rao, H Ma, Y Hao, H Wang arXiv preprint arXiv:2411.17770, 2024 | | 2024 |
| Exploiting counter-examples for active learning with partial labels F Zhang, Y Ye, L Feng, Z Rao, J Zhu, M Kalander, C Gong, J Hao, B Han Machine Learning 113 (6), 3849-3868, 2024 | | 2024 |
| Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders Q Shentu, B Li, K Zhao, Y Shu, Z Rao, L Pan, B Yang, C Guo arXiv preprint arXiv:2405.15273, 2024 | | 2024 |
| Active Learning with Partial Labels F Zhang, J Ye, L Feng, Z Rao, J Zhu, M Kalander, C Gong, HAO Jianye, ... | | |
