Quanquan Gu
Impact in
- Computational Mathematics top 2%
- Artificial Intelligence top 0.5%
- Advanced Graph Neural Networks
- Topic Modeling
- Adversarial Robustness in Machine Learning
Papers in
-
- Stochastic Gradient Optimization Techniques 25
- Advanced Graph Neural Networks 13
- Domain Adaptation and Few-Shot Learning 12
- Machine Learning and ELM 11
- Adversarial Robustness in Machine Learning 9
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- Face and Expression Recognition 17
- Advanced Neural Network Applications 9
- Co-authors
- Jiawei Han (24 shared papers)Jie Zhou (12 shared papers)Zhenhui Li (6 shared papers)Xiao Yu (5 shared papers)Urvashi Khandelwal (3 shared papers)Xiang Ren (2 shared papers)Yizhou Sun (3 shared papers)Bradley Sturt (2 shared papers)
- Journals
- Nature Communications (3 papers)Journal of Machine Learning Research (2 papers)Materials Today Bio (2 papers)Proceedings of the National Academy of Sciences (2 papers)Preventive Medicine (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Quanquan Gu
143 papers receiving 4.9k citations
Quanquan Gu's Hit Papers
Peers
Comparison fields: 5 of 176
- Computational Mathematics 55
- Artificial Intelligence 2.8k
- Computer Vision and Pattern Recognition 1.2k
- Information Systems 1.1k
- Modeling and Simulation 190
Countries citing papers authored by Quanquan Gu
This map shows the geographic impact of Quanquan Gu'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 Quanquan Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quanquan Gu more than expected).
Fields of papers citing papers by Quanquan Gu
This network shows the impact of papers produced by Quanquan Gu. 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 Quanquan Gu. The network helps show where Quanquan Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Quanquan Gu, 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 150 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Personalized entity recommendation Hit paper breakdown → | 2014 | 569 |
| 2 | 2006 | 303 | |
| 3 | Generalized Fisher score for feature selection | 2011 | 202 |
| 4 | 2010 | 199 | |
| 5 | 2009 | 198 | |
| 6 | Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States Hit paper breakdown → | 2022 | 185 |
| 7 | Improving Adversarial Robustness Requires Revisiting Misclassified Examples | 2020 | 163 |
| 8 | 2013 | 159 | |
| 9 | Joint Feature Selection and Subspace Learning | 2011 | 155 |
| 10 | 2019 | 145 | |
| 11 | 2009 | 132 | |
| 12 | 2020 | 113 | |
| 13 | 2014 | 102 | |
| 14 | 2012 | 102 | |
| 15 | 2011 | 85 | |
| 16 | 2012 | 78 | |
| 17 | 2020 | 74 | |
| 18 | 2014 | 71 | |
| 19 | Clustered Support Vector Machines | 2013 | 68 |
| 20 | Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization | 2018 | 66 |
About Quanquan Gu
Quanquan Gu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Statistics and Probability and Management Science and Operations Research, having authored 150 papers that have together received 5.0k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (28 papers), Stochastic Gradient Optimization Techniques (25 papers), Face and Expression Recognition (17 papers), Advanced Graph Neural Networks (13 papers), Domain Adaptation and Few-Shot Learning (12 papers), Machine Learning and ELM (11 papers), Advanced Neural Network Applications (9 papers) and Adversarial Robustness in Machine Learning (9 papers). The work is most often cited by research in Computational Mathematics (55 citations), Artificial Intelligence (2.8k citations), Computer Vision and Pattern Recognition (1.2k citations), Information Systems (1.1k citations) and Modeling and Simulation (190 citations). Quanquan Gu has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Jiawei Han, Jie Zhou, Zhenhui Li, Xiao Yu, Urvashi Khandelwal, Xiang Ren, Yizhou Sun, Bradley Sturt, Brandon Norick and Jiawei Han. Their work appears in journals such as Nature Communications, Journal of Machine Learning Research, Materials Today Bio, Proceedings of the National Academy of Sciences and Preventive Medicine.
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.