Haixu Wu

According to our database, Haixu Wu authored at least 20 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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

CoRR, 2024

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling.

Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Yunzhong Qiu, Li Zhang, Jianmin Wang, Mingsheng Long

CoRR, 2024

EuLagNet: Eulerian Fluid Prediction with Lagrangian Dynamics.

Qilong Ma, Haixu Wu, Lanxiang Xing, Jianmin Wang, Mingsheng Long

CoRR, 2024

Transolver: A Fast Transformer Solver for PDEs on General Geometries.

Haixu Wu, Huakun Luo, Haowen Wang, Jianmin Wang, Mingsheng Long

CoRR, 2024

2023

ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning.

Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long

IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

Interpretable weather forecasting for worldwide stations with a unified deep model.

Haixu Wu, Hang Zhou, Mingsheng Long, Jianmin Wang

Nat. Mac. Intell., June, 2023

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning.

Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long

IEEE Trans. Pattern Anal. Mach. Intell., 2023

HelmSim: Learning Helmholtz Dynamics for Interpretable Fluid Simulation.

Lanxiang Xing, Haixu Wu, Yuezhou Ma, Jianmin Wang, Mingsheng Long

CoRR, 2023

iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long

CoRR, 2023

SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling.

Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long

CoRR, 2023

SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling.

Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Solving High-Dimensional PDEs with Latent Spectral Models.

Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long

Proceedings of the International Conference on Machine Learning, 2023

TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting.

Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long

CoRR, 2022

Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting.

Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Supported Policy Optimization for Offline Reinforcement Learning.

Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Flowformer: Linearizing Transformers with Conservation Flows.

Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long

Proceedings of the International Conference on Machine Learning, 2022

Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy.

Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting.

Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions.

Haixu Wu, Zhiyu Yao, Jianmin Wang, Mingsheng Long

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021