Yuqiang Guan
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Statistical and Nonlinear Physics top 2%
- Molecular Biology
- Signal Processing top 5%
- Topics
- Advanced Clustering Algorithms Research (5 papers)Complex Network Analysis Techniques (3 papers)Gene expression and cancer classification (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputational MathematicsStatistical and Nonlinear Physics
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceDiscrete MathematicsJournal of Complexity
- Partner nations
- United States
In The Last Decade
Yuqiang Guan
9 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 1.1k
- Computer Vision and Pattern Recognition 806
- Statistical and Nonlinear Physics 416
- Molecular Biology 201
- Signal Processing 198
Countries citing papers authored by Yuqiang Guan
This map shows the geographic impact of Yuqiang Guan'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 Yuqiang Guan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuqiang Guan more than expected).
Fields of papers citing papers by Yuqiang Guan
This network shows the impact of papers produced by Yuqiang Guan. 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 Yuqiang Guan. The network helps show where Yuqiang Guan may publish in the future.
Co-authorship network of co-authors of Yuqiang Guan
This figure shows the co-authorship network connecting the top 25 collaborators of Yuqiang Guan. A scholar is included among the top collaborators of Yuqiang Guan 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 Yuqiang Guan. Yuqiang Guan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Weighted Graph Cuts without Eigenvectors A Multilevel Approachbreakdown → | 635 |
| 2 | 76 | |
| 3 | Kernel k-meansbreakdown → | 736 |
| 4 | 47 | |
| 5 | 196 | |
| 6 | 7 | |
| 7 | 4 | |
| 8 | 90 | |
| 9 | Refining clusters in high dimensional text data | 18 |
About Yuqiang Guan
Yuqiang Guan is a scholar working on Computer Graphics and Computer-Aided Design, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 9 papers that have together received 1.8k indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (5 papers), Complex Network Analysis Techniques (3 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (806 citations), Computational Mathematics (20 citations) and Statistical and Nonlinear Physics (416 citations). Yuqiang Guan has collaborated with scholars based in United States. Frequent co-authors include Inderjit S. Dhillon, Brian Kulis, Suvrit Sra, Hyuk Cho, Elise de Doncker and Kenneth Williams. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Discrete Mathematics and Journal of Complexity.
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.