MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions. - Haixu Wu; Zhiyu Yao; Jianmin Wang 001; Mingsheng Long (CVPR, 2021)

Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. - Haixu Wu; Jiehui Xu; Jianmin Wang 001; Mingsheng Long (NeurIPS, 2021)

Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. - Jiehui Xu; Haixu Wu; Jianmin Wang 001; Mingsheng Long (ICLR, 2022)

Flowformer: Linearizing Transformers with Conservation Flows. - Haixu Wu; Jialong Wu 001; Jiehui Xu; Jianmin Wang 001; Mingsheng Long (ICML, 2022)

Supported Policy Optimization for Offline Reinforcement Learning. - Jialong Wu 001; Haixu Wu; Zihan Qiu; Jianmin Wang 001; Mingsheng Long (NeurIPS, 2022)

Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting. - Yong Liu; Haixu Wu; Jianmin Wang 001; Mingsheng Long (NeurIPS, 2022)

Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting. - Yong Liu; Haixu Wu; Jianmin Wang 001; Mingsheng Long (CoRR, 2022)

TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. - Haixu Wu; Tengge Hu; Yong Liu; Hang Zhou; Jianmin Wang 001; Mingsheng Long (ICLR, 2023)

Solving High-Dimensional PDEs with Latent Spectral Models. - Haixu Wu; Tengge Hu; Huakun Luo; Jianmin Wang 001; Mingsheng Long (ICML, 2023)

SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling. - Jiaxiang Dong; Haixu Wu; Haoran Zhang; Li Zhang 065; Jianmin Wang 001; Mingsheng Long (NeurIPS, 2023)

HelmSim: Learning Helmholtz Dynamics for Interpretable Fluid Simulation. - Lanxiang Xing; Haixu Wu; Yuezhou Ma; Jianmin Wang 001; Mingsheng Long (CoRR, 2023)

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. - Yunbo Wang; Haixu Wu; Jianjin Zhang; Zhifeng Gao; Jianmin Wang 001; Philip S. Yu; Mingsheng Long (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Interpretable weather forecasting for worldwide stations with a unified deep model. - Haixu Wu; Hang Zhou; Mingsheng Long; Jianmin Wang 001 (Nat. Mac. Intell., 2023)

ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning. - Zhiyu Yao; Yunbo Wang; Haixu Wu; Jianmin Wang 001; Mingsheng Long (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

iTransformer: Inverted Transformers Are Effective for Time Series Forecasting. - Yong Liu; Tengge Hu; Haoran Zhang; Haixu Wu; Shiyu Wang 001; Lintao Ma; Mingsheng Long (ICLR, 2024)

TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting. - Shiyu Wang 001; Haixu Wu; Xiaoming Shi 001; Tengge Hu; Huakun Luo; Lintao Ma; James Y. Zhang; Jun Zhou 011 (ICLR, 2024)

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling. - Jiaxiang Dong; Haixu Wu; Yuxuan Wang 007; Yunzhong Qiu; Li Zhang 065; Jianmin Wang 001; Mingsheng Long (ICML, 2024)

Transolver: A Fast Transformer Solver for PDEs on General Geometries. - Haixu Wu; Huakun Luo; Haowen Wang; Jianmin Wang 001; Mingsheng Long (ICML, 2024)

HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction. - Lanxiang Xing; Haixu Wu; Yuezhou Ma; Jianmin Wang 001; Mingsheng Long (ICML, 2024)

Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers. - Zhiyu Yao; Jian Wang 066; Haixu Wu; Jingdong Wang 001; Mingsheng Long (ICML, 2024)

DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction. - Qilong Ma; Haixu Wu; Lanxiang Xing; Shangchen Miao; Mingsheng Long (NeurIPS, 2024)

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables. - Yuxuan Wang 007; Haixu Wu; Jiaxiang Dong; Guo Qin; Haoran Zhang; Yong Liu; Yunzhong Qiu; Jianmin Wang 001; Mingsheng Long (NeurIPS, 2024)

RoPINN: Region Optimized Physics-Informed Neural Networks. - Haixu Wu; Huakun Luo; Yuezhou Ma; Jianmin Wang 001; Mingsheng Long (NeurIPS, 2024)

EuLagNet: Eulerian Fluid Prediction with Lagrangian Dynamics. - Qilong Ma; Haixu Wu; Lanxiang Xing; Jianmin Wang 001; Mingsheng Long (CoRR, 2024)

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables. - Yuxuan Wang 007; Haixu Wu; Jiaxiang Dong; Yong Liu; Yunzhong Qiu; Haoran Zhang; Jianmin Wang 001; Mingsheng Long (CoRR, 2024)

Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers. - Hang Zhou; Yuezhou Ma; Haixu Wu; Haowen Wang; Mingsheng Long (CoRR, 2024)

Deep Time Series Models: A Comprehensive Survey and Benchmark. - Yuxuan Wang 007; Haixu Wu; Jiaxiang Dong; Yong Liu; Mingsheng Long; Jianmin Wang 001 (CoRR, 2024)

Metadata Matters for Time Series: Informative Forecasting with Transformers. - Jiaxiang Dong; Haixu Wu; Yuxuan Wang 007; Li Zhang 065; Jianmin Wang 001; Mingsheng Long (CoRR, 2024)

ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks. - Haixu Wu; Yuezhou Ma; Hang Zhou; Huikun Weng; Jianmin Wang 001; Mingsheng Long (CoRR, 2025)

Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries. - Huakun Luo; Haixu Wu; Hang Zhou; Lanxiang Xing; Yichen Di; Jianmin Wang 001; Mingsheng Long (CoRR, 2025)

FlashBias: Fast Computation of Attention with Bias. - Haixu Wu; Minghao Guo; Yuezhou Ma; Yuanxu Sun; Jianmin Wang 001; Wojciech Matusik; Mingsheng Long (CoRR, 2025)

PhySense: Sensor Placement Optimization for Accurate Physics Sensing. - Yuezhou Ma; Haixu Wu; Hang Zhou; Huikun Weng; Jianmin Wang 001; Mingsheng Long (CoRR, 2025)