Linnan Wang
Impact in
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
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- Advanced Neural Network Applications
Papers in
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- Advanced Neural Network Applications 5
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- Domain Adaptation and Few-Shot Learning 2
- Stochastic Gradient Optimization Techniques 2
- Privacy-Preserving Technologies in Data 1
- Co-authors
- Renqiang Min (1 shared paper)Srimat Chakradhar (1 shared paper)Yi Yang (1 shared paper)Rodrigo Fonseca (3 shared papers)Yuandong Tian (2 shared papers)Yiyang Zhao (2 shared papers)Teng Li (1 shared paper)Saining Xie (1 shared paper)
- Journals
- Neural Networks (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesNorwayChina
In The Last Decade
Linnan Wang
7 papers receiving 191 citations
Peers
Comparison fields: 5 of 69
- Hardware and Architecture 29
- Computer Vision and Pattern Recognition 80
- Computational Mathematics 2
- Artificial Intelligence 106
- Media Technology 13
Countries citing papers authored by Linnan Wang
This map shows the geographic impact of Linnan 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 Linnan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linnan Wang more than expected).
Fields of papers citing papers by Linnan Wang
This network shows the impact of papers produced by Linnan 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 Linnan Wang. The network helps show where Linnan Wang may publish in the future.
Co-authors
The 23 scholars most cited alongside Linnan 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
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 75 | |
| 2 | 2020 | 34 | |
| 3 | 2021 | 34 | |
| 4 | 2018 | 22 | |
| 5 | 2018 | 14 | |
| 6 | 2020 | 9 | |
| 7 | 2017 | 9 |
About Linnan Wang
Linnan Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture and Computational Mechanics, having authored 7 papers that have together received 197 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Domain Adaptation and Few-Shot Learning (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Parallel Computing and Optimization Techniques (2 papers), Advanced Data Storage Technologies (2 papers), Interconnection Networks and Systems (1 paper), Sparse and Compressive Sensing Techniques (1 paper) and Privacy-Preserving Technologies in Data (1 paper). The work is most often cited by research in Hardware and Architecture (29 citations), Computer Vision and Pattern Recognition (80 citations), Computational Mathematics (2 citations), Artificial Intelligence (106 citations) and Media Technology (13 citations). Linnan Wang has collaborated with scholars based in United States, Norway and China. Frequent co-authors include Renqiang Min, Srimat Chakradhar, Yi Yang, Rodrigo Fonseca, Yuandong Tian, Yiyang Zhao, Teng Li, Saining Xie, Wei Wu and George Bosilca. Their work appears in journals such as Neural Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence and Proceedings of the AAAI Conference on Artificial Intelligence.
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.