| A kernel two-sample test A Gretton, KM Borgwardt, MJ Rasch, B Schölkopf, A Smola The journal of machine learning research 13 (1), 723-773, 2012 | 7613 | 2012 |
| A kernel method for the two-sample-problem A Gretton, K Borgwardt, M Rasch, B Schölkopf, A Smola Advances in neural information processing systems 19, 2006 | 3133 | 2006 |
| Correcting sample selection bias by unlabeled data J Huang, A Gretton, K Borgwardt, B Schölkopf, A Smola Advances in neural information processing systems 19, 2006 | 2430 | 2006 |
| Demystifying mmd gans M Bińkowski, DJ Sutherland, M Arbel, A Gretton arXiv preprint arXiv:1801.01401, 2018 | 2413 | 2018 |
| Measuring statistical dependence with Hilbert-Schmidt norms A Gretton, O Bousquet, A Smola, B Schölkopf International conference on algorithmic learning theory, 63-77, 2005 | 2383 | 2005 |
| Integrating structured biological data by kernel maximum mean discrepancy KM Borgwardt, A Gretton, MJ Rasch, HP Kriegel, B Schölkopf, AJ Smola Bioinformatics 22 (14), e49-e57, 2006 | 2028 | 2006 |
| A kernel statistical test of independence A Gretton, K Fukumizu, C Teo, L Song, B Schölkopf, A Smola Advances in neural information processing systems 20, 2007 | 1291 | 2007 |
| A Hilbert space embedding for distributions A Smola, A Gretton, L Song, B Schölkopf International conference on algorithmic learning theory, 13-31, 2007 | 1111 | 2007 |
| Hilbert space embeddings and metrics on probability measures BK Sriperumbudur, A Gretton, K Fukumizu, B Schölkopf, GRG Lanckriet The Journal of Machine Learning Research 11, 1517-1561, 2010 | 1004 | 2010 |
| Ranking on data manifolds D Zhou, J Weston, A Gretton, O Bousquet, B Schölkopf Advances in neural information processing systems 16, 2003 | 1003 | 2003 |
| Equivalence of distance-based and RKHS-based statistics in hypothesis testing D Sejdinovic, B Sriperumbudur, A Gretton, K Fukumizu The annals of statistics, 2263-2291, 2013 | 974 | 2013 |
| Covariate shift by kernel mean matching A Gretton, A Smola, J Huang, M Schmittfull, K Borgwardt, B Schölkopf Dataset shift in machine learning 3 (4), 5, 2009 | 945 | 2009 |
| Optimal kernel choice for large-scale two-sample tests A Gretton, D Sejdinovic, H Strathmann, S Balakrishnan, M Pontil, ... Advances in neural information processing systems 25, 2012 | 933 | 2012 |
| Kernel measures of conditional dependence K Fukumizu, A Gretton, X Sun, B Schölkopf Advances in neural information processing systems 20, 2007 | 853 | 2007 |
| Feature selection via dependence maximization L Song, A Smola, A Gretton, J Bedo, K Borgwardt The Journal of Machine Learning Research 13 (1), 1393-1434, 2012 | 566 | 2012 |
| Kernel methods for measuring independence A Gretton, R Herbrich, A Smola, O Bousquet, B Schölkopf MIT Press, 2005 | 552 | 2005 |
| Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information A Belitski, A Gretton, C Magri, Y Murayama, MA Montemurro, ... Journal of Neuroscience 28 (22), 5696-5709, 2008 | 511 | 2008 |
| Supervised feature selection via dependence estimation L Song, A Smola, A Gretton, KM Borgwardt, J Bedo Proceedings of the 24th international conference on Machine learning, 823-830, 2007 | 507 | 2007 |
| On the empirical estimation of integral probability metrics BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet | 428 | 2012 |
| A kernel test of goodness of fit K Chwialkowski, H Strathmann, A Gretton International conference on machine learning, 2606-2615, 2016 | 423 | 2016 |
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
