Qingyun Sun
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Plant Science
- Information Systems top 10%
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Jianxin LiPhilip S. YuHao PengJia WuJun XuWangpeng AnHaoqian WangLifang He
- Topics
- Advanced Graph Neural Networks (15 papers)Topic Modeling (6 papers)Graph Theory and Algorithms (4 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern RecognitionJournal of Animal Science
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Qingyun Sun
38 papers receiving 656 citations
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 350
- Computer Vision and Pattern Recognition 156
- Plant Science 78
- Information Systems 76
- Statistical and Nonlinear Physics 63
Countries citing papers authored by Qingyun Sun
This map shows the geographic impact of Qingyun Sun'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 Qingyun Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingyun Sun more than expected).
Fields of papers citing papers by Qingyun Sun
This network shows the impact of papers produced by Qingyun Sun. 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 Qingyun Sun. The network helps show where Qingyun Sun may publish in the future.
Co-authorship network of co-authors of Qingyun Sun
This figure shows the co-authorship network connecting the top 25 collaborators of Qingyun Sun. A scholar is included among the top collaborators of Qingyun Sun based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Qingyun Sun. Qingyun Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 15 | |
| 11 | 10 | |
| 12 | 7 | |
| 13 | 10 | |
| 14 | 5 | |
| 15 | 3 | |
| 16 | 3 | |
| 17 | 24 | |
| 18 | 51 | |
| 19 | Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory | 0 |
| 20 | Convolutional Imputation of Matrix Networks | 2 |
About Qingyun Sun
Qingyun Sun is a scholar working on General Energy, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 46 papers that have together received 665 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (15 papers), Topic Modeling (6 papers) and Graph Theory and Algorithms (4 papers). The work is most often cited by research in Artificial Intelligence (350 citations), Computer Vision and Pattern Recognition (156 citations) and Statistical and Nonlinear Physics (63 citations). Qingyun Sun has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jianxin Li, Philip S. Yu, Hao Peng, Jia Wu, Jun Xu, Wangpeng An, Haoqian Wang, Lifang He, Qionghai Dai and Cheng Ji. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Journal of Animal Science.
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.