Bernhard Schölkopf

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Alex SmolaBoson AIVerified email at smola.org
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
Dominik JanzingAmazon Development Center, TuebingenVerified email at amazon.com
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Olivier ChapelleGoogleVerified email at chapelle.cc
Jason WestonMetaVerified email at fb.com
Stefan BauerHelmholtz | TUM | CIFARVerified email at tum.de
John C. PlattGoogleVerified email at google.com
Sebastian MikaVerified email at sebastianmika.info
Jonas PetersProfessor of Statistics, ETH ZurichVerified email at stat.math.ethz.ch
Francesco LocatelloAssistant Professor, ISTAVerified email at ista.ac.at
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)Verified email at cmu.edu
Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Michael HirschMax Planck Institute for Intelligent Systems TübingenVerified email at tuebingen.mpg.de
Moritz Grosse-WentrupUniversity of ViennaVerified email at univie.ac.at
Olivier BousquetGoogleVerified email at m4x.org
Krikamol MuandetCISPA - Helmholtz Center for Information SecurityVerified email at cispa.de
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryVerified email at biochem.mpg.de
Manuel Gomez RodriguezFaculty, Max Planck Institute for Software Systems (MPI-SWS)Verified email at mpi-sws.org

Bernhard Schölkopf

Director, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETH

Verified email at tuebingen.mpg.de

Machine Learning Causal Inference Artificial Intelligence Computational Photography Statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Learning with kernels: support vector machines, regularization, optimization, and beyond B Schölkopf, AJ Smola MIT press, 2002	25093*	2002
A tutorial on support vector regression AJ Smola, B Schölkopf Statistics and computing 14, 199-222, 2004	15975	2004
Nonlinear component analysis as a kernel eigenvalue problem B Schölkopf, A Smola, KR Müller Neural computation 10 (5), 1299-1319, 1998	11178	1998
Semi-supervised learning O Chapelle, B Schölkopf, A Zien MIT Press, 2006	8066*	2006
Estimating the support of a high-dimensional distribution B Schölkopf, JC Platt, J Shawe-Taylor, AJ Smola, RC Williamson Neural computation 13 (7), 1443-1471, 2001	7650	2001
Support vector machines MA Hearst, ST Dumais, E Osuna, J Platt, B Scholkopf IEEE Intelligent Systems and their applications 13 (4), 18-28, 1998	6943	1998
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	6275	2012
Learning with local and global consistency D Zhou, O Bousquet, T Lal, J Weston, B Schölkopf Advances in neural information processing systems 16, 2003	5613	2003
An introduction to kernel-based learning algorithms KR Muller, S Mika, G Ratsch, K Tsuda, B Scholkopf IEEE Transactions on Neural Networks 12 (2), 181-201, 2001	5077*	2001
Advances in kernel methods: support vector learning B Schölkopf, A Burges, C.J.C.: Smola The MIT press, 1999	4470*	1999
Fisher discriminant analysis with kernels S Mika, G Rätsch, J Weston, B Schölkopf, K Müller Neural networks for signal processing IX, 1999	4271	1999
Kernel principal component analysis B Schölkopf, A Smola, KR Müller International conference on artificial neural networks, 583-588, 1997	3836	1997
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3617	2000
Support vector method for novelty detection B Schölkopf, RC Williamson, A Smola, J Shawe-Taylor, J Platt Advances in neural information processing systems 12, 1999	3260	1999
Kernel methods in machine learning T Hofmann, B Schölkopf, AJ Smola Annals of Statistics 36 (3), 1171-1220, 2008	3032	2008
A gene expression map of Arabidopsis thaliana development M Schmid, TS Davison, SR Henz, UJ Pape, M Demar, M Vingron, ... Nature genetics 37 (5), 501-506, 2005	2832	2005
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	2785	2006
Elements of causal inference: foundations and learning algorithms J Peters, D Janzing, B Schölkopf The MIT Press, 2017	2414	2017
A generalized representer theorem B Schölkopf, R Herbrich, AJ Smola International conference on computational learning theory, 416-426, 2001	2388	2001
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	2259	2006

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