wuhx23@mails.tsinghua.edu.cn
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 learning and scientific machine learning, especially sequence modeling, physical world modeling and PDE solving. The goal of my research is to create strong foundation models through scientific inspiration and theoretical support for modeling our ever-changing world, solving challenging science problems and advancing practical applications.
Google Scholar / Semantic Scholar / GitHub / CV
Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers
Zhou Hang*
, Yuezhou Ma*
, Haixu Wu#, Haowen Wang, Mingsheng Long#
arXiv 2024
Deep Time Series Models: A Comprehensive Survey and Benchmark
Yuxuan Wang*
, Haixu Wu*
, Jiaxiang Dong*
, Yong Liu, Mingsheng Long#, Jianmin Wang
arXiv 2024
Metadata Matters for Time Series: Informative Forecasting with Transformers
Jiaxiang Dong*
, Haixu Wu*
, Yuxuan Wang*
, Li Zhang, Jianmin Wang, Mingsheng Long#
arXiv 2024
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, WAIC Youth Outstanding Paper Nomination)
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, Hot Paper)
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning
Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long#
TPAMI 2023 / PDF / Code
RoPINN: Region Optimized Physics-Informed Neural Networks
Haixu Wu, Huakun Luo, Yuezhou Ma, Jianmin Wang, Mingsheng Long#
NeurIPS 2024 / PDF / Code / Slides
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
Qilong Ma*
, Haixu Wu*
, Lanxiang Xing, Shangchen Miao, Mingsheng Long#
NeurIPS 2024 / PDF / Code / Slides
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#
NeurIPS 2024 / PDF / Code / Slides
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)
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
Lanxiang Xing*
, Haixu Wu*
, Yuezhou Ma, Jianmin Wang, Mingsheng Long#
ICML 2024 / PDF / Code / Slides
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
Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers
Zhiyu Yao, Jian Wang, Haixu Wu, Jingdong Wang, Mingsheng Long#
ICML 2024 / PDF / Code
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, Citation Rank 14th in ICLR 2024)
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
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)
Solving High-Dimensional PDEs with Latent Spectral Models
Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long#
ICML 2023 / PDF / Code / Slides
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 (Citation Rank 11th in ICLR 2023)
Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting
Yong Liu*
, Haixu Wu*
, Jianmin Wang, Mingsheng Long#
NeurIPS 2022 / PDF / Code / Slides
Supported Policy Optimization for Offline Reinforcement Learning
Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long#
NeurIPS 2022 / PDF / Code / Slides
Flowformer: Linearizing Transformers with Conservation Flows
Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long#
ICML 2022 / PDF / Code / Slides
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
Jiehui Xu*
, Haixu Wu*
, Jianmin Wang, Mingsheng Long#
ICLR 2022 / PDF / Code / Slides (Spotlight Paper, Citation Rank 15th in ICLR 2022)
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long#
NeurIPS 2021 / PDF / Code / Slides (PaperDigest Most Influential Paper)
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