Meng Ye
Impact in
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- Rings, Modules, and Algebras
- Advanced Topics in Algebra
- Commutative Algebra and Its Applications
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
Papers in
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- Domain Adaptation and Few-Shot Learning 4
- Quantum Computing Algorithms and Architecture 2
- Machine Learning and ELM 2
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- Multimodal Machine Learning Applications 2
- Co-authors
- Yuhong Guo (3 shared papers)Tongsuo Wu (5 shared papers)Karan Sikka (3 shared papers)Hong Cai (1 shared paper)Ajay Divakaran (4 shared papers)Bo Sun (1 shared paper)Qiong Liu (2 shared papers)Yeon-Chang Lee (1 shared paper)
- Journals
- Semigroup Forum (1 paper)Wireless Communications and Mobile Computing (1 paper)The China Quarterly (1 paper)Journal of Algebra and Its Applications (2 papers)Filomat (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Meng Ye
17 papers receiving 210 citations
Peers
Comparison fields: 5 of 59
- Algebra and Number Theory 42
- Computer Vision and Pattern Recognition 101
- Artificial Intelligence 135
- Discrete Mathematics and Combinatorics 13
- Media Technology 15
Countries citing papers authored by Meng Ye
This map shows the geographic impact of Meng Ye'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 Meng Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meng Ye more than expected).
Fields of papers citing papers by Meng Ye
This network shows the impact of papers produced by Meng Ye. 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 Meng Ye. The network helps show where Meng Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Meng Ye, 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 | 71 | |
| 2 | 2019 | 55 | |
| 3 | 2012 | 32 | |
| 4 | 2023 | 11 | |
| 5 | 2008 | 11 | |
| 6 | 2014 | 6 | |
| 7 | 2019 | 6 | |
| 8 | 2014 | 6 | |
| 9 | 2023 | 5 | |
| 10 | 2022 | 4 | |
| 11 | 2021 | 2 | |
| 12 | 2023 | 2 | |
| 13 | 2020 | 2 | |
| 14 | 2015 | 1 | |
| 15 | 2021 | 1 | |
| 16 | 2025 | 1 | |
| 17 | 2011 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2011 | 0 | |
| 20 | 2022 | 0 |
About Meng Ye
Meng Ye is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Algebra and Number Theory, Computer Networks and Communications and Sociology and Political Science, having authored 20 papers that have together received 218 indexed citations. Recurring topics across this work include Rings, Modules, and Algebras (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Commutative Algebra and Its Applications (3 papers), Advanced Topics in Algebra (3 papers), Quantum Computing Algorithms and Architecture (2 papers), COVID-19 diagnosis using AI (2 papers), Machine Learning and ELM (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Algebra and Number Theory (42 citations), Computer Vision and Pattern Recognition (101 citations), Artificial Intelligence (135 citations), Discrete Mathematics and Combinatorics (13 citations) and Media Technology (15 citations). Meng Ye has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Yuhong Guo, Tongsuo Wu, Karan Sikka, Hong Cai, Ajay Divakaran, Bo Sun, Qiong Liu, Yeon-Chang Lee, Srijan Kumar and Kartik Sharma. Their work appears in journals such as Semigroup Forum, Wireless Communications and Mobile Computing, The China Quarterly, Journal of Algebra and Its Applications and Filomat.
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.