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Arthur Gretton

Active 2002–2026

220
Papers
28,301
Citations
65
h-index
147
i10-index

Citations

Citations per year for Arthur Gretton1966: 1 citations1976: 2 citations1982: 2 citations1991: 1 citations1997: 2 citations2001: 1 citations2003: 4 citations2004: 15 citations2005: 31 citations2006: 50 citations2007: 91 citations2008: 189 citations2009: 270 citations2010: 275 citations2011: 372 citations2012: 420 citations2013: 523 citations2014: 540 citations2015: 623 citations2016: 759 citations2017: 809 citations2018: 1,028 citations2019: 1,382 citations2020: 1,824 citations2021: 1,897 citations2022: 1,234 citations2023: 984 citations2024: 1,059 citations2025: 876 citations2026: 261 citations1967–1975: no citations, so these years are not shown1977–1981: no citations, so these years are not shown1983–1990: no citations, so these years are not shown1992–1996: no citations, so these years are not shown1998–2000: no citations, so these years are not shown2002: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 3,671 citing papers, 27.1% of this breakdownUnited States: 2,980 citing papers, 22% of this breakdownUnited Kingdom: 874 citing papers, 6.5% of this breakdownGermany: 725 citing papers, 5.4% of this breakdownAustralia: 519 citing papers, 3.8% of this breakdownFrance: 493 citing papers, 3.6% of this breakdownJapan: 437 citing papers, 3.2% of this breakdownCanada: 406 citing papers, 3% of this breakdownHong Kong: 362 citing papers, 2.7% of this breakdownSingapore: 316 citing papers, 2.3% of this breakdownIndia: 223 citing papers, 1.7% of this breakdownItaly: 212 citing papers, 1.6% of this breakdown
0%27.1%Other 17.1%

Institutions

Fields

  • Computer Science66%
  • Engineering9.9%
  • Mathematics5.9%
  • Neuroscience4.8%
  • Biochemistry, Genetics and Molecular Biology3.1%
  • Physics and Astronomy2%
  • Other8.3%

Topics

  • Domain Adaptation and Few-Shot Learning7.2%
  • Face and Expression Recognition3%
  • Multimodal Machine Learning Applications2.9%
  • Generative Adversarial Networks and Image Synthesis2.8%
  • Anomaly Detection Techniques and Applications2.3%
  • Machine Learning and ELM2.1%
  • Other79.7%

Coauthors

All papers

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  1. Demystifying MMD GANs

    Authors: Mikolaj Binkowski, Danica J. Sutherland, Michael Arbel, Arthur Gretton - ICLR (Poster) 2018 cited by 2,110

  2. A Kernel Method for the Two-Sample Problem

    Authors: Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola - The MIT Press eBooks, NIPS 2006 cited by 2,657

  3. Integrating structured biological data by Kernel Maximum Mean Discrepancy

    Authors: Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola - Bioinformatics, ISMB (Supplement of Bioinformatics) 2006 cited by 1,710

  4. Measuring Statistical Dependence with Hilbert-Schmidt Norms

    Authors: Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf - Lecture notes in computer science, ALT 2005 cited by 1,575

  5. Correcting Sample Selection Bias by Unlabeled Data

    Authors: Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf - The MIT Press eBooks, NIPS 2006 cited by 1,918

  6. Equivalence of distance-based and RKHS-based statistics in hypothesis testing

    Authors: Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu - The Annals of Statistics 2012 cited by 593

  7. Optimal kernel choice for large-scale two-sample tests

    Authors: Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu - http://www.stat.berkeley.edu/%7Esbalakri/Papers/MMD12.pdf, NIPS 2012 cited by 764

  8. A Hilbert Space Embedding for Distributions

    Authors: Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf - Lecture notes in computer science, ALT 2007 cited by 747

  9. A Kernel Two-Sample Test

    Authors: Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola - J. Mach. Learn. Res. 2012 cited by 2,231

  10. A note on integral probability metrics and phi -divergences

    Authors: Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf - arXiv (Cornell University), CoRR 2009 cited by 121

  11. On the empirical estimation of integral probability metrics

    Authors: Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert Lanckriet - Electronic Journal of Statistics 2012 cited by 237

  12. A Kernel Statistical Test of Independence

    Authors: Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola - NIPS 2007 cited by 1,068

  13. Covariate Shift by Kernel Mean Matching

    Authors: Arthur Gretton, AJ Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, Bernhard Schölkopf - The MIT Press eBooks 2008 cited by 404

  14. Supervised Feature Selection via Dependence Estimation

    Authors: Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo - conference on Machine learning, ICML 2007 cited by 359

  15. Feature Selection via Dependence Maximization

    Authors: Le Song, Alexander J. Smola, Arthur Gretton, Justin Bedo, Karsten M. Borgwardt - J. Mach. Learn. Res. 2012 cited by 346

  16. Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models

    Authors: Le Song, Kenji Fukumizu, Arthur Gretton - IEEE Signal Processing Magazine, IEEE Signal Process. Mag. 2013 cited by 212

  17. Hilbert Space Embeddings and Metrics on Probability Measures

    Authors: Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet - Journal of Machine Learning Research, J. Mach. Learn. Res. 2010 cited by 484

  18. Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy

    Authors: Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton - ICLR (Poster) 2017 cited by 293

  19. Large-scale kernel methods for independence testing

    Authors: Qinyi Zhang, Sarah Filippi, Arthur Gretton, Dino Sejdinovic - Statistics and Computing, Stat. Comput. 2017 cited by 95

  20. Learning Deep Features in Instrumental Variable Regression

    Authors: Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton - ICLR 2021 cited by 90

  21. 31st International Conference on Machine Learning, ICML 2014

    Authors: Dino Sejdinović, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton - International Conference on Machine Learning 2014 cited by 108

  22. Learning-Order Autoregressive Models with Application to Molecular Graph Generation

    Authors: Zhe Wang, Jiaxin Shi, Nicolas Heess, Arthur Gretton, Michalis K. Titsias - ICML 2025 cited by 31

  23. (De)-regularized Maximum Mean Discrepancy Gradient Flow

    Authors: Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur - J. Mach. Learn. Res. 2025 cited by 13

  24. Kernel Methods for Measuring Independence

    Authors: Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf - J. Mach. Learn. Res. 2005 cited by 344