Arthur Gretton

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Alex SmolaAmazon Web ServicesVerified email at smola.org
Kenji FukumizuThe Institute of Statistical MathematicsVerified email at ism.ac.jp
Karsten BorgwardtProfessor, ETH ZurichVerified email at bsse.ethz.ch
Le SongGeorgia Institute of TechnologyVerified email at cc.gatech.edu
Bharath SriperumbudurPennsylvania State UniversityVerified email at psu.edu
Malte J RaschIBM Research AIVerified email at ibm.com
Dino SejdinovicAssociate Professor, University of OxfordVerified email at stats.ox.ac.uk
Nikos LogothetisVisiting Professor of Neuroscience, Stanford UniversityVerified email at stanford.edu
Olivier BousquetGoogleVerified email at m4x.org
Ralf HerbrichHasso Plattner InstituteVerified email at hpi.de
Michael ArbelInria - Univ. Grenoble AlpesVerified email at inria.fr
Heiko StrathmannResearch Scientist at DeepmindVerified email at deepmind.com
Gert LanckrietProfessor, UCSDVerified email at eng.ucsd.edu
Danica J. SutherlandUniversity of British ColumbiaVerified email at cs.ubc.ca
Matthew BlaschkoKU LeuvenVerified email at esat.kuleuven.be
Zoltan SzaboProfessor, LSEVerified email at lse.ac.uk
Hans-Peter KriegelProfessor für Informatik, Ludwig-Maximilians-University MunichVerified email at dbs.ifi.lmu.de
Wittawat JitkrittumGoogle ResearchVerified email at google.com
Massimiliano PontilIstituto Italiano di Tecnologia & University College LondonVerified email at iit.it

Arthur Gretton

Gatsby Computational Neuroscience Unit, UCL

Verified email at gatsby.ucl.ac.uk - Homepage

generative models causality hypothesis testing kernel methods machine learning


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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	3346	2012
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	1667	2006
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	1661	2006
Measuring statistical dependence with Hilbert-Schmidt norms A Gretton, O Bousquet, A Smola, B Schölkopf International conference on algorithmic learning theory, 63-77, 2005	1376	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	1060	2006
Ranking on data manifolds D Zhou, J Weston, A Gretton, O Bousquet, B Schölkopf Advances in neural information processing systems 16, 2003	916	2003
A Hilbert space embedding for distributions A Smola, A Gretton, L Song, B Schölkopf International Conference on Algorithmic Learning Theory, 13-31, 2007	800	2007
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	689	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	616	2010
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	575	2009
Kernel measures of conditional dependence K Fukumizu, A Gretton, X Sun, B Schölkopf Advances in neural information processing systems 20, 2007	526	2007
Demystifying mmd gans M Bińkowski, DJ Sutherland, M Arbel, A Gretton arXiv preprint arXiv:1801.01401, 2018	510	2018
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	493	2013
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	471	2012
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	426	2008
Kernel methods for measuring independence A Gretton, R Herbrich, A Smola, O Bousquet, B Schölkopf MIT Press, 2005	372	2005
Feature Selection via Dependence Maximization. L Song, A Smola, A Gretton, J Bedo, K Borgwardt Journal of Machine Learning Research 13 (5), 2012	362	2012
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	354	2007
Statistical Consistency of Kernel Canonical Correlation Analysis. K Fukumizu, FR Bach, A Gretton Journal of Machine Learning Research 8 (2), 2007	285	2007
Inferring spike trains from local field potentials MJ Rasch, A Gretton, Y Murayama, W Maass, NK Logothetis Journal of neurophysiology 99 (3), 1461-1476, 2008	236	2008

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