Haixu Wu

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wuhx23@mails.tsinghua.edu.cn

About Me

I am currently a Ph.D. student (from fall, 2020) in School of Software, Tsinghua University, under the supervision of Prof. Mingsheng Long.
My research interests lie in deep and scientific learning, especially science-inspired model architectures. My research goal is to model this ever-changing and non-stationary world through scientific and interpretable deep models. Besides, I also devote myself to promoting research to valuable real-world applications.

Google Scholar / Semantic Scholar / GitHub / CV

Education

Highlights

Preprints

  1. RoPINN: Region Optimized Physics-Informed Neural Networks
    Haixu Wu, Huakun Luo, Yuezhou Ma, Jianmin Wang, Mingsheng Long#
    arXiv 2024

  2. Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers
    Zhou Hang, Yuezhou Ma, Haixu Wu#, Haowen Wang, Mingsheng Long#
    arXiv 2024

  3. EuLagNet: Eulerian Fluid Prediction with Lagrangian Dynamics
    Qilong Ma*, Haixu Wu*, Lanxiang Xing, Jianmin Wang, Mingsheng Long#
    arXiv 2024

  4. TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
    Yuxuan Wang*, Haixu Wu*, Jiaxiang Dong, Yong Liu, Yunzhong Qiu, Haoran Zhang, Jianmin Wang, Mingsheng Long#
    arXiv 2024

Journal Articles

  1. Interpretable Weather Forecasting for Worldwide Stations with a Unified Deep Model
    Haixu Wu, Hang Zhou, Mingsheng Long#, Jianmin Wang#
    Nature Machine Intelligence 2023 / PDF / Code / Slides (Cover Article)

  2. PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
    Yunbo Wang*, Haixu Wu*, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long#
    TPAMI 2022 / PDF / Code (ESI Highly Cited Paper)

  3. ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning
    Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long#
    TPAMI 2023 / PDF / Code

Conference Proceedings

  1. Transolver: A Fast Transformer Solver for PDEs on General Geometries
    Haixu Wu, Huakun Luo, Haowen Wang, Jianmin Wang, Mingsheng Long#
    ICML 2024 / PDF / Code / Slides / Poster (Spotlight Paper)

  2. HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
    Lanxiang Xing*, Haixu Wu*, Yuezhou Ma, Jianmin Wang, Mingsheng Long#
    ICML 2024 / PDF / Code / Slides

  3. TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
    Jiaxiang Dong*, Haixu Wu*, Yuxuan Wang, Yunzhong Qiu, Li Zhang, Jianmin Wang, Mingsheng Long#
    ICML 2024 / PDF / Code / Slides

  4. Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers
    Zhiyu Yao, Jian Wang, Haixu Wu, Jingdong Wang, Mingsheng Long#
    ICML 2024 / PDF

  5. iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
    Yong Liu*, Tengge Hu*, Haoran Zhang*, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long#
    ICLR 2024 / PDF / Code / Slides (Spotlight Paper)

  6. TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
    Shiyu Wang*, Haixu Wu*, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou
    ICLR 2024 / PDF / Code / Slides

  7. SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
    Jiaxiang Dong*, Haixu Wu*, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long#
    NeurIPS 2023 / PDF / Code (Spotlight Paper)

  8. Solving High-Dimensional PDEs with Latent Spectral Models
    Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long#
    ICML 2023 / PDF / Code / Slides

  9. TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
    Haixu Wu*, Tengge Hu*, Yong Liu*, Hang Zhou, Jianmin Wang, Mingsheng Long#
    ICLR 2023 / PDF / Code / Slides

  10. Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting
    Yong Liu*, Haixu Wu*, Jianmin Wang, Mingsheng Long#
    NeurIPS 2022 / PDF / Code / Slides

  11. Supported Policy Optimization for Offline Reinforcement Learning
    Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long#
    NeurIPS 2022 / PDF / Code / Slides

  12. Flowformer: Linearizing Transformers with Conservation Flows
    Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long#
    ICML 2022 / PDF / Code / Slides

  13. Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
    Jiehui Xu*, Haixu Wu*, Jianmin Wang, Mingsheng Long#
    ICLR 2022 / PDF / Code / Slides (Spotlight Paper)

  14. Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
    Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long#
    NeurIPS 2021 / PDF / Code / Slides (Rank 10th in NeurIPS 2021)

  15. MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions
    Haixu Wu*, Zhiyu Yao*, Jianmin Wang, Mingsheng Long#
    CVPR 2021 / PDF / Appendix / Code / Slides

* Equal Contribution, # Corresponding Author

System and Applications

Experience

Selected Awards