Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting H Wu, J Xu, J Wang, M Long Advances in Neural Information Processing Systems (NeurIPS), 2021 | 1172 | 2021 |
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy J Xu, H Wu, J Wang, M Long International Conference on Learning Representations (ICLR), 2021 | 325 | 2021 |
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis H Wu, T Hu, Y Liu, H Zhou, J Wang, M Long International Conference on Learning Representations (ICLR), 2022 | 284 | 2022 |
PredRNN: A recurrent neural network for spatiotemporal predictive learning Y Wang, H Wu, J Zhang, Z Gao, J Wang, P Yu, M Long IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 | 262 | 2022 |
Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting Y Liu, H Wu, J Wang, M Long Advances in Neural Information Processing Systems (NeurIPS), 2022 | 208* | 2022 |
MotionRNN: A flexible model for video prediction with spacetime-varying motions H Wu, Z Yao, J Wang, M Long IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 122 | 2021 |
iTransformer: Inverted transformers are effective for time series forecasting Y Liu, T Hu, H Zhang, H Wu, S Wang, L Ma, M Long International Conference on Learning Representations (ICLR), 2023 | 81 | 2023 |
Flowformer: Linearizing Transformers with Conservation Flows H Wu, J Wu, J Xu, J Wang, M Long International Conference on Machine Learning (ICML), 2022 | 54 | 2022 |
Supported Policy Optimization for Offline Reinforcement Learning J Wu, H Wu, Z Qiu, J Wang, M Long Advances in Neural Information Processing Systems (NeurIPS), 2022 | 38 | 2022 |
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling J Dong, H Wu, H Zhang, L Zhang, J Wang, M Long Advances in Neural Information Processing Systems (NeurIPS), 2023 | 33 | 2023 |
Interpretable weather forecasting for worldwide stations with a unified deep model H Wu, H Zhou, M Long, J Wang Nature Machine Intelligence 5 (6), 602-611, 2023 | 22 | 2023 |
Solving High-Dimensional PDEs with Latent Spectral Models H Wu, T Hu, H Luo, J Wang, M Long International Conference on Machine Learning (ICML), 2023 | 18 | 2023 |
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning Z Yao, Y Wang, H Wu, J Wang, M Long IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 | 5 | 2023 |
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables Y Wang, H Wu, J Dong, Y Liu, Y Qiu, H Zhang, J Wang, M Long arXiv preprint arXiv:2402.19072, 2024 | 2 | 2024 |
Transolver: A Fast Transformer Solver for PDEs on General Geometries H Wu, H Luo, H Wang, J Wang, M Long International Conference on Machine Learning (ICML), 2024 | 2 | 2024 |
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling J Dong, H Wu, Y Wang, Y Qiu, L Zhang, J Wang, M Long International Conference on Machine Learning (ICML), 2024 | 1 | 2024 |
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting S Wang, H Wu, X Shi, T Hu, H Luo, L Ma, JY Zhang, J Zhou International Conference on Learning Representations (ICLR), 2023 | 1 | 2023 |
EuLagNet: Eulerian Fluid Prediction with Lagrangian Dynamics Q Ma, H Wu, L Xing, J Wang, M Long arXiv preprint arXiv:2402.02425, 2024 | | 2024 |
HelmSim: Learning Helmholtz Dynamics for Interpretable Fluid Simulation L Xing, H Wu, Y Ma, J Wang, M Long International Conference on Machine Learning (ICML), 2023 | | 2023 |