Arthur Gretton
Impact in
- Statistics and Probability top 0.1%
- Statistical Methods and Inference
- Artificial Intelligence top 0.05%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and ELM
- Anomaly Detection Techniques and Applications
- Neural Networks and Applications
- Gaussian Processes and Bayesian Inference
Papers in
-
- Neural Networks and Applications 39
- Gaussian Processes and Bayesian Inference 32
- Bayesian Methods and Mixture Models 20
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- Statistical Methods and Inference 30
- Advanced Statistical Methods and Models 11
- Statistical Methods and Bayesian Inference 9
- Co-authors
- Bernhard Schölkopf (33 shared papers)Karsten Borgwardt (17 shared papers)Alex Smola (17 shared papers)Alexander J. Smola (7 shared papers)Malte J. Rasch (6 shared papers)Kenji Fukumizu (30 shared papers)Olivier Bousquet (4 shared papers)Le Song (15 shared papers)
- Journals
- Journal of Machine Learning Research (9 papers)Bioinformatics (2 papers)Magnetic Resonance Imaging (2 papers)Neural Computation (2 papers)Machine Learning (2 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Arthur Gretton
129 papers receiving 12.3k citations
Arthur Gretton's Hit Papers
Peers
Comparison fields: 5 of 190
- Statistics and Probability 1.8k
- Artificial Intelligence 7.3k
- Computer Vision and Pattern Recognition 4.0k
- Signal Processing 1.1k
- Cognitive Neuroscience 1.0k
Countries citing papers authored by Arthur Gretton
This map shows the geographic impact of Arthur Gretton'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 Arthur Gretton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arthur Gretton more than expected).
Fields of papers citing papers by Arthur Gretton
This network shows the impact of papers produced by Arthur Gretton. 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 Arthur Gretton. The network helps show where Arthur Gretton may publish in the future.
Co-authors
The 25 scholars most cited alongside Arthur Gretton, 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 135 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Kernel Method for the Two-Sample-Problem Hit paper breakdown → | 2007 | 1340 |
| 2 | Integrating structured biological data by Kernel Maximum Mean Discrepancy Hit paper breakdown → | 2006 | 1241 |
| 3 | Correcting Sample Selection Bias by Unlabeled Data Hit paper breakdown → | 2007 | 1114 |
| 4 | A kernel two-sample test Hit paper breakdown → | 2012 | 1108 |
| 5 | Measuring Statistical Dependence with Hilbert-Schmidt Norms Hit paper breakdown → | 2005 | 970 |
| 6 | Ranking on Data Manifolds Hit paper breakdown → | 2003 | 523 |
| 7 | A Hilbert Space Embedding for Distributions Hit paper breakdown → | 2007 | 432 |
| 8 | Equivalence of distance-based and RKHS-based statistics in hypothesis testing Hit paper breakdown → | 2013 | 348 |
| 9 | Optimal kernel choice for large-scale two-sample tests Hit paper breakdown → | 2012 | 347 |
| 10 | A Kernel Statistical Test of Independence | 2007 | 342 |
| 11 | 2008 | 326 | |
| 12 | Correcting sample selection bias by unlabeled data | 2007 | 272 |
| 13 | 2007 | 269 | |
| 14 | Kernel Measures of Conditional Dependence | 2007 | 243 |
| 15 | 2010 | 239 | |
| 16 | 2008 | 237 | |
| 17 | Feature selection via dependence maximization | 2012 | 235 |
| 18 | Kernel Methods for Measuring Independence | 2005 | 205 |
| 19 | 2007 | 175 | |
| 20 | 2007 | 174 |
About Arthur Gretton
Arthur Gretton is a scholar working on Artificial Intelligence, Statistics and Probability, Signal Processing, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 135 papers that have together received 12.8k indexed citations. Recurring topics across this work include Neural Networks and Applications (39 papers), Gaussian Processes and Bayesian Inference (32 papers), Statistical Methods and Inference (30 papers), Blind Source Separation Techniques (20 papers), Bayesian Methods and Mixture Models (20 papers), Face and Expression Recognition (15 papers), Advanced Statistical Methods and Models (11 papers) and Statistical Methods and Bayesian Inference (9 papers). The work is most often cited by research in Statistics and Probability (1.8k citations), Artificial Intelligence (7.3k citations), Computer Vision and Pattern Recognition (4.0k citations), Signal Processing (1.1k citations) and Cognitive Neuroscience (1.0k citations). Arthur Gretton has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Bernhard Schölkopf, Karsten Borgwardt, Alex Smola, Alexander J. Smola, Malte J. Rasch, Kenji Fukumizu, Olivier Bousquet, Le Song, Bharath K. Sriperumbudur and Jiayuan Huang. Their work appears in journals such as Journal of Machine Learning Research, Bioinformatics, Magnetic Resonance Imaging, Neural Computation and Machine Learning.
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.