Arthur Gretton

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHPatvirtintas el. paštas tuebingen.mpg.de
Alex SmolaBoson AIPatvirtintas el. paštas smola.org
Kenji FukumizuThe Institute of Statistical MathematicsPatvirtintas el. paštas ism.ac.jp
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryPatvirtintas el. paštas biochem.mpg.de
Bharath SriperumbudurPennsylvania State UniversityPatvirtintas el. paštas psu.edu
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligencePatvirtintas el. paštas biomap.com
Malte J RaschSony AI (previously: IBM Research AI)Patvirtintas el. paštas sony.com
Dino SejdinovicProfessor of Statistical Machine Learning, University of AdelaidePatvirtintas el. paštas adelaide.edu.au
Michael ArbelInria - Univ. Grenoble AlpesPatvirtintas el. paštas inria.fr
Danica J. SutherlandUniversity of British Columbia + AmiiPatvirtintas el. paštas cs.ubc.ca
Nikos LogothetisDirector of International Center for Primate Brain Research, Shanghai, ChinaPatvirtintas el. paštas stanford.edu
Olivier BousquetGooglePatvirtintas el. paštas m4x.org
Heiko StrathmannResearch Scientist at DeepmindPatvirtintas el. paštas deepmind.com
Ralf HerbrichHasso Plattner InstitutePatvirtintas el. paštas hpi.de
Gert LanckrietProfessor, UCSDPatvirtintas el. paštas eng.ucsd.edu
Matthew BlaschkoKU LeuvenPatvirtintas el. paštas esat.kuleuven.be
Zoltan SzaboProfessor, LSEPatvirtintas el. paštas lse.ac.uk
Hans-Peter KriegelProfessor für Informatik, Ludwig-Maximilians-University MunichPatvirtintas el. paštas dbs.ifi.lmu.de
Wittawat JitkrittumGoogle ResearchPatvirtintas el. paštas google.com
Mikołaj BińkowskiResearch Scientist, DeepMindPatvirtintas el. paštas google.com

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Arthur Gretton

Gatsby Computational Neuroscience Unit and Google Deepmind

Patvirtintas el. paštas gatsby.ucl.ac.uk - Pagrindinis puslapis

generative models causality hypothesis testing kernel methods machine learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	6233	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	2779	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	2254	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	2109	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	1828	2006
Demystifying mmd gans M Bińkowski, DJ Sutherland, M Arbel, A Gretton arXiv preprint arXiv:1801.01401, 2018	1708	2018
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	1120	2007
A Hilbert space embedding for distributions A Smola, A Gretton, L Song, B Schölkopf International conference on algorithmic learning theory, 13-31, 2007	1058	2007
Ranking on data manifolds D Zhou, J Weston, A Gretton, O Bousquet, B Schölkopf Advances in neural information processing systems 16, 2003	999	2003
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	905	2010
Covariate shift by kernel mean matching A Gretton, A Smola, J Huang, M Schmittfull, K Borgwardt, B Schölkopf	861	2008
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	839	2012
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	812	2013
Kernel measures of conditional dependence K Fukumizu, A Gretton, X Sun, B Schölkopf Advances in neural information processing systems 20, 2007	760	2007
Feature Selection via Dependence Maximization. L Song, A Smola, A Gretton, J Bedo, K Borgwardt Journal of Machine Learning Research 13 (5), 2012	510	2012
Kernel methods for measuring independence. A Gretton, R Herbrich, A Smola, O Bousquet, B Schölkopf, A Hyvärinen Journal of Machine Learning Research 6 (12), 2005	489	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	488	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	479	2007
On the empirical estimation of integral probability metrics BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet	374	2012
A kernel test of goodness of fit K Chwialkowski, H Strathmann, A Gretton International conference on machine learning, 2606-2615, 2016	371	2016

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