Jianmin Wang
Impact in
- Computer Vision and Pattern Recognition top 0.05%
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Image Retrieval and Classification Techniques
- Advanced Neural Network Applications
- Artificial Intelligence top 0.05%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and ELM
- Anomaly Detection Techniques and Applications
Papers in
-
- Domain Adaptation and Few-Shot Learning 49
-
- Service-Oriented Architecture and Web Services 38
- Co-authors
- Mingsheng Long (79 shared papers)Philip S. Yu (34 shared papers)Guiguang Ding (23 shared papers)Zhangjie Cao (21 shared papers)Jiaguang Sun (22 shared papers)Yue Cao (11 shared papers)Michael I. Jordan (10 shared papers)Yunbo Wang (13 shared papers)
- Journals
- Proceedings of the VLDB Endowment (13 papers)IEEE Transactions on Knowledge and Data Engineering (13 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (7 papers)Designs Codes and Cryptography (5 papers)Computers in Industry (4 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Jianmin Wang
426 papers receiving 15.1k citations
Jianmin Wang's Hit Papers
Peers
Comparison fields: 5 of 195
- Computer Vision and Pattern Recognition 6.5k
- Artificial Intelligence 7.0k
- Signal Processing 1.1k
- Management Information Systems 791
- Information Systems 1.5k
Countries citing papers authored by Jianmin Wang
This map shows the geographic impact of Jianmin Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jianmin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianmin Wang more than expected).
Fields of papers citing papers by Jianmin Wang
This network shows the impact of papers produced by Jianmin Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jianmin Wang. The network helps show where Jianmin Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jianmin Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 457 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Transfer Feature Learning with Joint Distribution Adaptation Hit paper breakdown → | 2013 | 1457 |
| 2 | Multi-Adversarial Domain Adaptation Hit paper breakdown → | 2018 | 584 |
| 3 | Transfer Joint Matching for Unsupervised Domain Adaptation Hit paper breakdown → | 2014 | 523 |
| 4 | Transferable Representation Learning with Deep Adaptation Networks Hit paper breakdown → | 2018 | 502 |
| 5 | Adaptation Regularization: A General Framework for Transfer Learning Hit paper breakdown → | 2013 | 487 |
| 6 | HashNet: Deep Learning to Hash by Continuation Hit paper breakdown → | 2017 | 457 |
| 7 | Deep Hashing Network for Efficient Similarity Retrieval Hit paper breakdown → | 2016 | 452 |
| 8 | PredRNN: recurrent neural networks for predictive learning using spatiotemporal LSTMs Hit paper breakdown → | 2017 | 418 |
| 9 | Semantics-preserving hashing for cross-view retrieval Hit paper breakdown → | 2015 | 412 |
| 10 | PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning Hit paper breakdown → | 2022 | 338 |
| 11 | Partial Transfer Learning with Selective Adversarial Networks Hit paper breakdown → | 2018 | 319 |
| 12 | Universal Domain Adaptation Hit paper breakdown → | 2019 | 313 |
| 13 | Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics Hit paper breakdown → | 2019 | 306 |
| 14 | 2018 | 250 | |
| 15 | Skilful nowcasting of extreme precipitation with NowcastNet Hit paper breakdown → | 2023 | 245 |
| 16 | 2019 | 211 | |
| 17 | 2019 | 205 | |
| 18 | 2007 | 202 | |
| 19 | 2016 | 198 | |
| 20 | 2017 | 191 |
About Jianmin Wang
Jianmin Wang is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 457 papers that have together received 15.4k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (49 papers), Business Process Modeling and Analysis (42 papers), Service-Oriented Architecture and Web Services (38 papers), Multimodal Machine Learning Applications (33 papers), Advanced Database Systems and Queries (32 papers), Advanced Image and Video Retrieval Techniques (29 papers), Time Series Analysis and Forecasting (27 papers) and Data Quality and Management (26 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (6.5k citations), Artificial Intelligence (7.0k citations), Signal Processing (1.1k citations), Management Information Systems (791 citations) and Information Systems (1.5k citations). Jianmin Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Mingsheng Long, Philip S. Yu, Guiguang Ding, Zhangjie Cao, Jiaguang Sun, Yue Cao, Michael I. Jordan, Yunbo Wang, Zijia Lin and Han Zhu. Their work appears in journals such as Proceedings of the VLDB Endowment, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Pattern Analysis and Machine Intelligence, Designs Codes and Cryptography and Computers in Industry.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.