Arthur Gretton
Impact in
- Statistics and Probability top 0.2%
- Statistical Methods and Inference
- Advanced Statistical Methods and Models
- Artificial Intelligence top 0.2%
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Applications
- Gaussian Processes and Bayesian Inference
- Anomaly Detection Techniques and Applications
Papers in
-
- Statistical Methods and Inference 28
- Advanced Statistical Methods and Models 11
- Statistical Methods and Bayesian Inference 9
-
- Neural Networks and Applications 33
- Gaussian Processes and Bayesian Inference 22
- Bayesian Methods and Mixture Models 17
- Co-authors
- Bernhard SchölkopfKarsten BorgwardtKenji FukumizuMalte J. RaschAlex SmolaBharath K. SriperumbudurAlexander J. SmolaLe Song
- Journals
- Journal of Machine Learning Research (9 papers)Bioinformatics (2 papers)Machine Learning (2 papers)Biometrika (2 papers)Neural Computation (2 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Arthur Gretton
110 papers receiving 7.2k citations
Hit Papers
Peers
Comparison fields: 5 of 185
- Statistics and Probability 1.3k
- Artificial Intelligence 3.9k
- Computer Vision and Pattern Recognition 2.1k
- Signal Processing 678
- Cognitive Neuroscience 823
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
| # | Work | ||
|---|---|---|---|
| 1 | Stein's Method Meets Statistics: A Review of Some Recent Developments | 2021 | 3 |
| 2 | A Non-Asymptotic Analysis for Stein Variational Gradient Descent | 2020 | 3 |
| 3 | On gradient regularizers for MMD GANs | 2018 | 7 |
| 4 | Density Estimation in Infinite Dimensional Exponential Families | 2017 | 16 |
| 5 | 31st International Conference on Machine Learning, ICML 2014 | 2014 | 74 |
| 6 | B-test: A Non-parametric, Low Variance Kernel Two-sample Test | 2013 | 18 |
| 7 | B -tests: low variance kernel two-sample tests | 2013 | 5 |
| 8 | Consistent Nonparametric Tests of Independence | 2010 | 63 |
| 9 | Nonparametric Tree Graphical Models. | 2010 | 14 |
| 10 | Nonlinear directed acyclic structure learning with weakly additive noise models | 2009 | 24 |
| 11 | 2008 | 1 | |
| 12 | Characteristic Kernels on Groups and Semigroups | 2008 | 43 |
| 13 | Learning Taxonomies by Dependence Maximization | 2008 | 13 |
| 14 | Injective hilbert space embeddings of probability measures | 2008 | 73 |
| 15 | Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis | 2008 | 4 |
| 16 | Fast kernel ICA using an approximate Newton method | 2007 | 7 |
| 17 | A Kernel Statistical Test of Independence | 2007 | 317 |
| 18 | Colored Maximum Variance Unfolding | 2007 | 56 |
| 19 | Kernel Constrained Covariance for Dependence Measurement | 2005 | 24 |
| 20 | Estimating the Leave-One-Out Error for Classification Learning with SVMs | 2001 | 3 |
About Arthur Gretton
Arthur Gretton is a scholar working on Statistics and Probability, Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition and Analytical Chemistry, having authored 116 papers that have together received 7.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (33 papers), Statistical Methods and Inference (28 papers), Gaussian Processes and Bayesian Inference (22 papers), Blind Source Separation Techniques (19 papers), Bayesian Methods and Mixture Models (17 papers), Face and Expression Recognition (11 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 (1.3k citations), Artificial Intelligence (3.9k citations), Computer Vision and Pattern Recognition (2.1k citations), Signal Processing (678 citations) and Cognitive Neuroscience (823 citations). Arthur Gretton has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Bernhard Schölkopf, Karsten Borgwardt, Kenji Fukumizu, Malte J. Rasch, Alex Smola, Bharath K. Sriperumbudur, Alexander J. Smola, Le Song, Hans‐Peter Kriegel and Dino Sejdinović. Their work appears in journals such as Journal of Machine Learning Research, Bioinformatics, Machine Learning, Biometrika and Neural Computation.
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.