World's Best Scientists 2026 revealed!
Mingsheng Long

Mingsheng Long

D-Index & Metrics

Computer Science

D-Index
64
Citations
29190
World Ranking
2522
National Ranking
341

Overview

Mingsheng Long is affiliated with Tsinghua University in China and specializes in the field of Computer Science. Their research contributions span multiple subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Management Science and Operations Research, and Atmospheric Science.

Their scholarly work has focused on several main topics, with notable emphasis on Domain Adaptation and Few-Shot Learning, Time Series Analysis and Forecasting, Multimodal Machine Learning Applications, Human Pose and Action Recognition, Topic Modeling, Machine Learning and Data Classification, and Stock Market Forecasting Methods.

Frequent co-authors collaborating with Mingsheng Long include Jianmin Wang, Haixu Wu, Ximei Wang, Zhangjie Cao, and Yunbo Wang.

The scientist has published extensively in various venues. The most frequent publication forums include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Scientia Sinica Informationis
  • Nature

Recent papers authored or co-authored by Mingsheng Long include:

  • "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting," 2021, arXiv (Cornell University)
  • "PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning," 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis," 2022, arXiv (Cornell University)
  • "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting," 2023, arXiv (Cornell University)

Their research often addresses complex problems in time series forecasting and spatiotemporal predictive learning, with a focus on transformer-based architectures and recurrent neural networks.

Best Publications

  • Learning Transferable Features with Deep Adaptation Networks

    Mingsheng Long;Mingsheng Long;Yue Cao;Jianmin Wang;Michael Jordan

  • Transfer Feature Learning with Joint Distribution Adaptation

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Jiaguang Sun

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

    haixu wu;Jiehui Xu;Jianmin Wang;Mingsheng Long

  • Deep transfer learning with joint adaptation networks

    Mingsheng Long;Han Zhu;Jianmin Wang;Michael I. Jordan

  • Conditional Adversarial Domain Adaptation

    Mingsheng Long;Zhangjie Cao;Jianmin Wang;Michael I. Jordan

  • Unsupervised domain adaptation with residual transfer networks

    Mingsheng Long;Han Zhu;Jianmin Wang;Michael I. Jordan

  • Multi-Adversarial Domain Adaptation

    Zhongyi Pei;Zhangjie Cao;Mingsheng Long;Jianmin Wang

  • Transfer Joint Matching for Unsupervised Domain Adaptation

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Jiaguang Sun

  • HashNet: Deep Learning to Hash by Continuation

    Zhangjie Cao;Mingsheng Long;Jianmin Wang;Philip S. Yu

  • Deep Hashing Network for efficient similarity retrieval

    Han Zhu;Mingsheng Long;Jianmin Wang;Yue Cao

  • Adaptation Regularization: A General Framework for Transfer Learning

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Sinno Jialin Pan

  • PredRNN: recurrent neural networks for predictive learning using spatiotemporal LSTMs

    Yunbo Wang;Mingsheng Long;Jianmin Wang;Zhifeng Gao

  • Transferable Representation Learning with Deep Adaptation Networks

    Mingsheng Long;Yue Cao;Zhangjie Cao;Jianmin Wang

  • PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning

    Yunbo Wang;Haixu Wu;Jianjin Zhang;Zhifeng Gao

  • Partial Adversarial Domain Adaptation

    Zhangjie Cao;Lijia Ma;Mingsheng Long;Jianmin Wang

  • Partial Transfer Learning with Selective Adversarial Networks

    Zhangjie Cao;Mingsheng Long;Jianmin Wang;Michael I. Jordan

  • Universal Domain Adaptation

    Kaichao You;Mingsheng Long;Zhangjie Cao;Jianmin Wang

  • Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics

    Yunbo Wang;Jianjin Zhang;Hongyu Zhu;Mingsheng Long

  • Transfer Learning with Graph Co-Regularization

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Dou Shen

  • Deep Cauchy Hashing for Hamming Space Retrieval

    Yue Cao;Mingsheng Long;Bin Liu;Jianmin Wang

  • Bridging Theory and Algorithm for Domain Adaptation.

    Yuchen Zhang;Tianle Liu;Mingsheng Long;Michael I. Jordan

  • Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation

    Xinyang Chen;Sinan Wang;Mingsheng Long;Jianmin Wang

  • Eidetic 3D LSTM: A Model for Video Prediction and Beyond

    Yunbo Wang;Yunbo Wang;Lu Jiang;Ming Hsuan Yang;Li Jia Li

Frequent Co-Authors

Jianmin Wang
Jianmin Wang Tsinghua University
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Guiguang Ding
Guiguang Ding Tsinghua University
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Han Hu
Han Hu Microsoft Research Asia (China)
Jingdong Wang
Jingdong Wang Baidu (China)
Xiang Zhang
Xiang Zhang University of Hong Kong
Li Fei-Fei
Li Fei-Fei Stanford University
Jiajun Wu
Jiajun Wu Stanford University

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