Arthur Gretton
2002–2026 年に発表
- 220
- 論文数
- 28,301
- 被引用数
- 65
- h 指数
- 147
- i10 指数
被引用数
引用元
国・地域
機関
分野
- Computer Science66%
- Engineering9.9%
- Mathematics5.9%
- Neuroscience4.8%
- Biochemistry, Genetics and Molecular Biology3.1%
- Physics and Astronomy2%
- その他8.3%
トピック
- 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%
- その他79.7%
共著者
- Bernhard Schölkopf32
- Kenji Fukumizu32
- Bharath K. Sriperumbudur23
- Alexander J. Smola22
- Le Song19
- Dimitri Meunier14
- Dino Sejdinovic14
- Karsten M. Borgwardt13
- Arnaud Doucet12
- Liyuan Xu12
- Michael Arbel12
- Antonin Schrab10
- Danica J. Sutherland10
- Matthew B. Blaschko9
- Wittawat Jitkrittum9
- Zoltán Szabó9
- Heiko Strathmann8
- Alexandre Galashov7
- Gert R. G. Lanckriet6
- Houssam Zenati6
- Krikamol Muandet6
- Massimiliano Pontil6
- Zhu Li6
- Bariscan Bozkurt5
全論文
- Demystifying MMD GANs
著者: Mikolaj Binkowski, Danica J. Sutherland, Michael Arbel, Arthur Gretton - ICLR (Poster) 2018 被引用: 2,110
- A Kernel Method for the Two-Sample Problem
著者: Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola - The MIT Press eBooks, NIPS 2006 被引用: 2,657
- Integrating structured biological data by Kernel Maximum Mean Discrepancy
著者: Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola - Bioinformatics, ISMB (Supplement of Bioinformatics) 2006 被引用: 1,710
- Measuring Statistical Dependence with Hilbert-Schmidt Norms
著者: Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf - Lecture notes in computer science, ALT 2005 被引用: 1,575
- Correcting Sample Selection Bias by Unlabeled Data
著者: Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf - The MIT Press eBooks, NIPS 2006 被引用: 1,918
- Equivalence of distance-based and RKHS-based statistics in hypothesis testing
著者: Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu - The Annals of Statistics 2012 被引用: 593
- Optimal kernel choice for large-scale two-sample tests
著者: 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 被引用: 764
- A Hilbert Space Embedding for Distributions
著者: Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf - Lecture notes in computer science, ALT 2007 被引用: 747
- A Kernel Two-Sample Test
著者: Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola - J. Mach. Learn. Res. 2012 被引用: 2,231
- A note on integral probability metrics and phi -divergences
著者: Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf - arXiv (Cornell University), CoRR 2009 被引用: 121
- On the empirical estimation of integral probability metrics
著者: Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert Lanckriet - Electronic Journal of Statistics 2012 被引用: 237
- A Kernel Statistical Test of Independence
著者: Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola - NIPS 2007 被引用: 1,068
- Covariate Shift by Kernel Mean Matching
著者: Arthur Gretton, AJ Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, Bernhard Schölkopf - The MIT Press eBooks 2008 被引用: 404
- Supervised Feature Selection via Dependence Estimation
著者: Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo - conference on Machine learning, ICML 2007 被引用: 359
- Feature Selection via Dependence Maximization
著者: Le Song, Alexander J. Smola, Arthur Gretton, Justin Bedo, Karsten M. Borgwardt - J. Mach. Learn. Res. 2012 被引用: 346
- Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models
著者: Le Song, Kenji Fukumizu, Arthur Gretton - IEEE Signal Processing Magazine, IEEE Signal Process. Mag. 2013 被引用: 212
- Hilbert Space Embeddings and Metrics on Probability Measures
著者: Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet - Journal of Machine Learning Research, J. Mach. Learn. Res. 2010 被引用: 484
- Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
著者: Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton - ICLR (Poster) 2017 被引用: 293
- Large-scale kernel methods for independence testing
著者: Qinyi Zhang, Sarah Filippi, Arthur Gretton, Dino Sejdinovic - Statistics and Computing, Stat. Comput. 2017 被引用: 95
- Learning Deep Features in Instrumental Variable Regression
著者: Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton - ICLR 2021 被引用: 90
- 31st International Conference on Machine Learning, ICML 2014
著者: Dino Sejdinović, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton - International Conference on Machine Learning 2014 被引用: 108
- Learning-Order Autoregressive Models with Application to Molecular Graph Generation
著者: Zhe Wang, Jiaxin Shi, Nicolas Heess, Arthur Gretton, Michalis K. Titsias - ICML 2025 被引用: 31
- (De)-regularized Maximum Mean Discrepancy Gradient Flow
著者: Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur - J. Mach. Learn. Res. 2025 被引用: 13
- Kernel Methods for Measuring Independence
著者: Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf - J. Mach. Learn. Res. 2005 被引用: 344
