Mingsheng Long

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 186

Top Venues

Publications

Jialong Wu, Chaoyi Deng, Jianmin Wang, Mingsheng Long
Supercompiler Code Optimization with Zero-Shot Reinforcement Learning. CoRR (2024)
Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting. ICLR (2024)
Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, Mingsheng Long
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models. CoRR (2024)
Yong Liu, Haoran Zhang, Chenyu Li, Xiangdong Huang, Jianmin Wang, Mingsheng Long
Timer: Transformers for Time Series Analysis at Scale. CoRR (2024)
Li Liu, Timothy M. Hospedales, Yann LeCun, Mingsheng Long, Jiebo Luo, Wanli Ouyang, Matti Pietikäinen, Tinne Tuytelaars
Editorial: Learning With Fewer Labels in Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. 46 (3) (2024)
Qilong Ma, Haixu Wu, Lanxiang Xing, Jianmin Wang, Mingsheng Long
EuLagNet: Eulerian Fluid Prediction with Lagrangian Dynamics. CoRR (2024)
Hang Zhou, Yuezhou Ma, Haixu Wu, Haowen Wang, Mingsheng Long
Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers. CoRR (2024)
Jincheng Zhong, Xingzhuo Guo, Jiaxiang Dong, Mingsheng Long
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting. CoRR (2024)
Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Yong Liu, Mingsheng Long, Jianmin Wang
Deep Time Series Models: A Comprehensive Survey and Benchmark. CoRR (2024)
Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Yong Liu, Yunzhong Qiu, Haoran Zhang, Jianmin Wang, Mingsheng Long
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables. CoRR (2024)
Kaichao You, Guo Qin, Anchang Bao, Meng Cao, Ping Huang, Jiulong Shan, Mingsheng Long
Efficient ConvBN Blocks for Transfer Learning and Beyond. ICLR (2024)
Jialong Wu, Shaofeng Yin, Ningya Feng, Xu He, Dong Li, Jianye Hao, Mingsheng Long
iVideoGPT: Interactive VideoGPTs are Scalable World Models. CoRR (2024)
Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Yunzhong Qiu, Li Zhang, Jianmin Wang, Mingsheng Long
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling. CoRR (2024)
Zhiyu Yao, Xinyang Chen, Sinan Wang, Qinyan Dai, Yumeng Li, Tanchao Zhu, Mingsheng Long
Recommender Transformers with Behavior Pathways. WWW (2024)
Haixu Wu, Huakun Luo, Yuezhou Ma, Jianmin Wang, Mingsheng Long
RoPINN: Region Optimized Physics-Informed Neural Networks. CoRR (2024)
Kaichao You, Runsheng Bai, Meng Cao, Jianmin Wang, Ion Stoica, Mingsheng Long
depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers. CoRR (2024)
Haixu Wu, Huakun Luo, Haowen Wang, Jianmin Wang, Mingsheng Long
Transolver: A Fast Transformer Solver for PDEs on General Geometries. CoRR (2024)
Kaiyuan Chen, Xingzhuo Guo, Yu Zhang, Jianmin Wang, Mingsheng Long
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding. CoRR (2024)
Zhongyi Pei, Zhiyao Cen, Yipeng Huang, Chen Wang, Lin Liu, Philip S. Yu, Mingsheng Long, Jianmin Wang
BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization. KDD (2024)
Xingzhuo Guo, Junwei Pan, Ximei Wang, Baixu Chen, Jie Jiang, Mingsheng Long
On the Embedding Collapse when Scaling up Recommendation Models. CoRR (2023)
Jincheng Zhong, Haoyu Ma, Ximei Wang, Zhi Kou, Mingsheng Long
Bi-tuning: Efficient Transfer from Pre-trained Models. ECML/PKDD (5) (2023)
Haoyu Ma, Jialong Wu, Ningya Feng, Jianmin Wang, Mingsheng Long
Harmony World Models: Boosting Sample Efficiency for Model-based Reinforcement Learning. CoRR (2023)
Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling. CoRR (2023)
Zhangjie Cao, Kaichao You, Ziyang Zhang, Jianmin Wang, Mingsheng Long
From Big to Small: Adaptive Learning to Partial-Set Domains. IEEE Trans. Pattern Anal. Mach. Intell. 45 (2) (2023)
Yuchen Zhang, Mingsheng Long, Kaiyuan Chen, Lanxiang Xing, Ronghua Jin, Michael I. Jordan, Jianmin Wang
Skilful nowcasting of extreme precipitation with NowcastNet. Nat. 619 (7970) (2023)
Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45 (11) (2023)
Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long
CLIPood: Generalizing CLIP to Out-of-Distributions. ICML (2023)
Yong Liu, Chenyu Li, Jianmin Wang, Mingsheng Long
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors. CoRR (2023)
Haixu Wu, Hang Zhou, Mingsheng Long, Jianmin Wang
Interpretable weather forecasting for worldwide stations with a unified deep model. Nat. Mac. Intell. 5 (6) (2023)
Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long
Solving High-Dimensional PDEs with Latent Spectral Models. CoRR (2023)
Yong Liu, Chenyu Li, Jianmin Wang, Mingsheng Long
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors. NeurIPS (2023)
Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long
CLIPood: Generalizing CLIP to Out-of-Distributions. CoRR (2023)
Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long
Solving High-Dimensional PDEs with Latent Spectral Models. ICML (2023)
Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning. NeurIPS (2023)
Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning. CoRR (2023)
Kaichao You, Anchang Bao, Guo Qin, Meng Cao, Ping Huang, Jiulong Shan, Mingsheng Long
Tune-Mode ConvBN Blocks For Efficient Transfer Learning. CoRR (2023)
Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling. NeurIPS (2023)
Xingzhuo Guo, Yuchen Zhang, Jianmin Wang, Mingsheng Long
Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms. ICML (2023)
Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. ICLR (2023)
Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45 (2) (2023)
Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long
Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45 (12) (2023)
Lanxiang Xing, Haixu Wu, Yuezhou Ma, Jianmin Wang, Mingsheng Long
HelmSim: Learning Helmholtz Dynamics for Interpretable Fluid Simulation. CoRR (2023)
Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning. NeurIPS (2023)
Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting. CoRR (2023)
Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long
ForkMerge: Overcoming Negative Transfer in Multi-Task Learning. CoRR (2023)
Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models. CoRR (2022)
Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long
Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting. CoRR (2022)
Geng Chen, Wendong Zhang, Han Lu, Siyu Gao, Yunbo Wang, Mingsheng Long, Xiaokang Yang
Continual Predictive Learning from Videos. CoRR (2022)
Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models. NeurIPS (2022)
Zhiyu Yao, Yunbo Wang, Jianmin Wang, Philip S. Yu, Mingsheng Long
VideoDG: Generalizing Temporal Relations in Videos to Novel Domains. IEEE Trans. Pattern Anal. Mach. Intell. 44 (11) (2022)
Zhiyu Yao, Xinyang Chen, Sinan Wang, Qinyan Dai, Yumeng Li, Tanchao Zhu, Mingsheng Long
Recommender Transformers with Behavior Pathways. CoRR (2022)
Zhangjie Cao, Kaichao You, Ziyang Zhang, Jianmin Wang, Mingsheng Long
From Big to Small: Adaptive Learning to Partial-Set Domains. CoRR (2022)
Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model. ICLR (2022)
Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long
Supported Policy Optimization for Offline Reinforcement Learning. CoRR (2022)
Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long
Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting. NeurIPS (2022)
Yiwen Qiu, Jialong Wu, Zhangjie Cao, Mingsheng Long
Out-of-Dynamics Imitation Learning from Multimodal Demonstrations. CoRL (2022)
Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. CoRR (2022)
Chao Huang, Zhangjie Cao, Yunbo Wang, Jianmin Wang, Mingsheng Long
MetaSets: Meta-Learning on Point Sets for Generalizable Representations. CoRR (2022)
Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan, Jianmin Wang, Mingsheng Long
Debiased Self-Training for Semi-Supervised Learning. NeurIPS (2022)
Yiwen Qiu, Jialong Wu, Zhangjie Cao, Mingsheng Long
Out-of-Dynamics Imitation Learning from Multimodal Demonstrations. CoRR (2022)
Baixu Chen, Junguang Jiang, Ximei Wang, Jianmin Wang, Mingsheng Long
Debiased Pseudo Labeling in Self-Training. CoRR (2022)
Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long
Flowformer: Linearizing Transformers with Conservation Flows. CoRR (2022)
Kaichao You, Yong Liu, Ziyang Zhang, Jianmin Wang, Michael I. Jordan, Mingsheng Long
Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs. J. Mach. Learn. Res. 23 (2022)
Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. ICLR (2022)
Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long
Supported Policy Optimization for Offline Reinforcement Learning. NeurIPS (2022)
Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long
Flowformer: Linearizing Transformers with Conservation Flows. ICML (2022)
Geng Chen, Wendong Zhang, Han Lu, Siyu Gao, Yunbo Wang, Mingsheng Long, Xiaokang Yang
Continual Predictive Learning from Videos. CVPR (2022)
Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long
Transferability in Deep Learning: A Survey. CoRR (2022)
Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long
Decoupled Adaptation for Cross-Domain Object Detection. ICLR (2022)
Ximei Wang, Jinghan Gao, Jianmin Wang, Mingsheng Long
Self-Tuning for Data-Efficient Deep Learning. CoRR (2021)
Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long
Open Domain Generalization with Domain-Augmented Meta-Learning. CVPR (2021)
Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. CoRR (2021)
Haixu Wu, Zhiyu Yao, Jianmin Wang, Mingsheng Long
MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions. CVPR (2021)
Min-Ling Zhang, Sheng-Jun Huang, Mingsheng Long
Preface. J. Comput. Sci. Technol. 36 (3) (2021)
Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long
Open Domain Generalization with Domain-Augmented Meta-Learning. CoRR (2021)
Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang
Self-Tuning for Data-Efficient Deep Learning. ICML (2021)
Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning. CoRR (2021)
Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long
Regressive Domain Adaptation for Unsupervised Keypoint Detection. CoRR (2021)
Hong Liu, Jianmin Wang, Mingsheng Long
Cycle Self-Training for Domain Adaptation. CoRR (2021)
Bo Fu, Zhangjie Cao, Jianmin Wang, Mingsheng Long
Transferable Query Selection for Active Domain Adaptation. CVPR (2021)
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long
Zoo-Tuning: Adaptive Transfer from A Zoo of Models. ICML (2021)
Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. CoRR (2021)
Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long
Decoupled Adaptation for Cross-Domain Object Detection. CoRR (2021)
Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. CoRR (2021)
Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long
LogME: Practical Assessment of Pre-trained Models for Transfer Learning. ICML (2021)
Chao Huang, Zhangjie Cao, Yunbo Wang, Jianmin Wang, Mingsheng Long
MetaSets: Meta-Learning on Point Sets for Generalizable Representations. CVPR (2021)
Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model. CoRR (2021)
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long
Zoo-Tuning: Adaptive Transfer from a Zoo of Models. CoRR (2021)
Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. NeurIPS (2021)
Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long
Regressive Domain Adaptation for Unsupervised Keypoint Detection. CVPR (2021)
Hong Liu, Jianmin Wang, Mingsheng Long
Cycle Self-Training for Domain Adaptation. NeurIPS (2021)
Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Mingsheng Long
Omni-Training for Data-Efficient Deep Learning. CoRR (2021)
Kaichao You, Yong Liu, Mingsheng Long, Jianmin Wang
LogME: Practical Assessment of Pre-trained Models for Transfer Learning. CoRR (2021)
Haixu Wu, Zhiyu Yao, Mingsheng Long, Jianmin Wang
MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions. CoRR (2021)
Kaichao You, Yong Liu, Jianmin Wang, Michael I. Jordan, Mingsheng Long
Ranking and Tuning Pre-trained Models: A New Paradigm of Exploiting Model Hubs. CoRR (2021)
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Representation Subspace Distance for Domain Adaptation Regression. ICML (2021)
Hong Liu, Mingsheng Long, Jianmin Wang, Yu Wang
Learning to Adapt to Evolving Domains. NeurIPS (2020)
Ying Jin, Zhangjie Cao, Mingsheng Long, Jianmin Wang
Transferring Pretrained Networks to Small Data via Category Decorrelation. BMVC (2020)
Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu, Jiaguang Sun
Multi-Task Learning of Generalizable Representations for Video Action Recognition. ICME (2020)
Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks. CoRR (2020)

Mingsheng Long.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Mingsheng Long