Prof. Dr. Bernhard Schölkopf

Adresse: Spemannstr. 38
72076 Tübingen
Raum Nummer: 211
Tel.: 07071 601 551
Fax: 07071 601 552
E-Mail: bernhard.schoelkopf


Bild von Schölkopf, Bernhard, Prof. Dr.

Bernhard Schölkopf

Position: Direktor  Abteilung: Schölkopf

Note: We have moved to the MPI for Metals Research and are in the process of reorienting it into an MPI for Intelligent Systems (working title). For a press release in German, click here.


My scientific interests are in the field of inference from empirical data, in particular machine learning and perception, and I am head of the Department of Empirical Inference. In particular, I study kernel methods for extracting regularities from high-dimensional data. These regularities are usually statistical ones, however, in recent years I have also become interested in methods for finding causal regularities.

To learn more about our work, you may want to take a look at the Department Overview from the last report to our scientific advisory board, or at short project reports from the same document:


Many of the papers can downloaded if you click on the tab "publications;" the older ones usually from A starting point is the first chapter of our book Learning with Kernels, available online. If your interest in machine learning is a mathematical one, you might prefer our review paper in the Annals of Statistics (arXiv link). For a general audience, I wrote a short high-level introduction in German that appeared in the Jahrbuch of the Max Planck Society.

Click here for a photograph of a beautiful northern light, which I took a few years ago from the plane on the way home from NIPS.

Note: I am not very organized with my e-mail; if you want to apply for a position in my lab, please send your application only to

Bernhard Schölkopf was born in Stuttgart on 20 February, 1968. He received an M.Sc. in mathematics and the Lionel Cooper Memorial Prize from the University of London in 1992, followed in 1994 by the Diplom in physics from the Eberhard-Karls-Universität, Tübingen. Three years later, he obtained a doctorate in computer science from the Technical University Berlin. His thesis on Support Vector Learning won the annual dissertation prize of the German Association for Computer Science (GI). In 1998, he won the prize for the best scientific project at the German National Research Center for Computer Science (GMD). He has researched at AT&T Bell Labs, at GMD FIRST, Berlin, at the Australian National University, Canberra, and at Microsoft Research Cambridge (UK). He has taught at Humboldt University, Technical University Berlin, and Eberhard-Karls-University Tübingen. In July 2001, he was appointed scientific member of the Max Planck Society and director at the MPI for Biological Cybernetics; in October 2002, he was appointed Honorarprofessor for Machine Learning at the Technical University Berlin. In 2006, he received the J. K. Aggarwal Prize of the International Association for Pattern Recognition, in 2011, he got the Max Planck Research Award. The ISI lists him as a highly cited researcher. He served on the editorial boards of JMLR, IEEE PAMI, and IJCV.

He is on the boards of the NIPS foundation and of the International Machine Learning Society. Members of his department have won various awards at the major machine learning conference.
Some details:

Journal of Machine Learning Research is an online journal which he helped launch as a founding action editor in early 2000. JMLR is the flagship journal of machine learning.
International Journal of Computer Vision
, one of the two flagship journals of computer vision (with IEEE PAMI, see below)
IEEE Transactions on Pattern Analysis and Machine Intelligence

Information Science and Statistics
, a Springer series of monographs
Advances in Data Analysis and Classification

With 5-year impact factors (ISI, 2008) of 10.3 and 8.0, respectively, IJCV and PAMI are the two top journals in the general area of artificial intelligence (they are ranked three and five in all of computer science). JMLR is number four (5.9).

In addition, he has served and serves as PC member (e.g., NIPS, COLT, ICML, UAI, DAGM, CVPR, Snowbird Learning Workshop) and as (program) (co-)chair of various conferences (COLT'03, DAGM'04, NIPS'05 (click here for NIPS'05 author and reviewer information), as well as the first two kernel workshops). He acted as general chair of NIPS'06.

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Bücher (7):

Lu HH-S, Schölkopf B und Zhao H: Handbook of Statistical Bioinformatics, 627, Springer, Berlin, Germany, (2011). ISBN: 978-3-642-16344-9, Series: Springer Handbooks of Computational Statistics
Bakir GH, Hofmann T, Schölkopf B, Smola AJ, Taskar B und Vishwanathan SVN: Predicting Structured Data, 360, MIT Press, Cambridge, MA, USA, (September-2007). ISBN: 0-262-02617-1, Series: Advances in neural information processing systems
Chapelle O, Schölkopf B und Zien A: Semi-Supervised Learning, 508, MIT Press, Cambridge, MA, USA, (2006). ISBN: 0-262-25589-8
Schölkopf B, Tsuda K und Vert J-P: Kernel Methods in Computational Biology, 410, MIT Press, Cambridge, MA, USA, (August-2004). ISBN: 0-262-19509-7, Series: Computational Molecular Biology
Schölkopf B und Smola AJ: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, 644, MIT Press, Cambridge, MA, USA, (Dezember-2002). ISBN: 0-262-19457-9, Series: Adaptive Computation and Machine Learning
Schölkopf B, Burges CJC und Smola AJ: Advances in Kernel Methods: Support Vector Learning, 352, MIT Press, Cambridge, MA, USA, (1999). ISBN: 0-262-19416-3
Schölkopf B: Support vector learning, 173, Oldenbourg, München, Germany, (1997). ISBN: 3-486-24632-1

Tagungsbände (7):

Guyon I, Janzing D und Schölkopf B: Causality: Objectives and Assessment, Workshop on Causality: Objectives and Assessment at NIPS 2008 (COA '08), 288, International Machine Learning Society, Madison, WI, USA, (Dezember-2008).
-, Series: JMLR Workshop and Conference Proceedings ; 6
Schölkopf B, Platt J und Hofmann T: Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), 1690, MIT Press, Cambridge, MA, USA, (September-2007).
Weiss Y, Schölkopf B und Platt J: Advances in Neural Information Processing Systems 18: Proceedings of the 2006 Conference, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), 1676, MIT Press, Cambridge, MA, USA, (Mai-2006).
Rasmussen CE, Bülthoff HH, Giese MA und Schölkopf B: Pattern Recognition: 26th DAGM Symposium, 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), 581, Springer, Berlin, Germany, (September-2004).
978-3-540-22945-2, Series: Lecture Notes in Computer Science ; 3175
Thrun S, Saul LK und Schölkopf B: Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), 1621, MIT Press, Cambridge, MA, USA, (Juni-2004).
Schölkopf B und Warmuth MK: Learning Theory and Kernel Machines, 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), 746, Springer, Berlin, Germany, (August-2003).
978-3-540-40720-1, Series: Lecture Notes in Computer Science ; 2777
Buhmann J und Schölkopf B: Inference Principles and Model Selection, Dagstuhl Seminar 01301, 22, Leibniz-Zentrum für Informatik, Dagstuhl, Germany, (Juli-2001).

Artikel (103):

Loktyushin A, Ehses P, Schölkopf B und Scheffler K (September-2018) Autofocusing-based phase correction Magnetic Resonance in Medicine 80(3) 958-968.
Fomina T, Lohmann G, Erb M, Ethofer T, Schölkopf B und Grosse-Wentrup M (November-2016) Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS Journal of Neural Engineering 13(6:066021) 1-14.
Besserve M, Lowe SC, Logothetis NK, Schölkopf B und Panzeri S (September-2015) Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer PLoS Biology 13(9) 1-29.
Loktyushin A, Nickisch H, Pohmann R und Schölkopf B (April-2015) Blind multirigid retrospective motion correction of MR images Magnetic Resonance in Medicine 73(4) 1457–1468.
Küffner R, Zach N, Norel R, Hawe J, Schoenfeld D, Wang L, Li G, Fang L, Mackey L, Hardiman O, Cudkowicz M, Sherman A, Ertaylan G, Grosse-Wentrup M, Hothorn T, van Ligtenberg J, Macke JH, Meyer T, Schölkopf B, Tran L, Vaughan R, Stolovitzky G und Leitner ML (Januar-2015) Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression Nature Biotechnology 33(1) 51-57.
Muelling K, Boularias A, Mohler B, Schölkopf B und Peters J (Oktober-2014) Learning strategies in table tennis using inverse reinforcement learning Biological Cybernetics 108(5) 603-619.
Loktyuschin A, Nickisch H, Pohmann R und Schölkopf B (Dezember-2013) Blind Retrospective Motion Correction of MR Images Magnetic Resonance in Medicine 70(6) 1608–1618.
Soekadar SR, Born J, Birbaumer N, Bensch M, Halder S, Murguialday AR, Gharabaghi A, Nijboer F, Schölkopf B und Martens S (September-2013) Fragmentation of slow wave sleep after onset of complete locked-in state Journal of Clinical Sleep Medicine 9(9) 951-953.
Grosse-Wentrup M und Schölkopf B (Mai-2012) High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces Journal of Neural Engineering 9(4) 1-8.
Janzing D, Mooij J, Zhang K, Lemeire J, Zscheischler J, Daniušis P, Steudel B und Schölkopf B (Mai-2012) Information-geometric approach to inferring causal directions Artificial Intelligence 182-183 1-31.
Gretton A, Borgwardt K, Rasch M, Schölkopf B und Smola A (März-2012) A Kernel Two-Sample Test Journal of Machine Learning Research 13 723−773.
Hill NJ und Schölkopf B (Februar-2012) An online brain–computer interface based on shifting attention to concurrent streams of auditory stimuli Journal of Neural Engineering 9(2) 1-13.
Peters J, Janzing D und Schölkopf B (Dezember-2011) Causal Inference on Discrete Data using Additive Noise Models IEEE Transactions on Pattern Analysis and Machine Intelligence 33(12) 2436-2450.
Kitching T, Amara A, Gill M, Harmeling S, Heymans C, Massey R, Rowe B, Schrabback T, Voigt L, Balan S, Bernstein G, Bethge M, Bridle S, Courbin F, Gentile M, Heavens A, Hirsch M, Hosseini R, Kiessling A, Kirk D, Kuijken K, Mandelbaum R, Moghaddam B, Nurbaeva G, Paulin-Henriksson S, Rassat A, Rhodes J, Schölkopf B, Shawe-Taylor J, Shmakova M, Taylor A, Velander M, van Waerbeke L, Witherick D und Wittman D (September-2011) Gravitational Lensing Accuracy Testing 2010 (GREAT10) Challenge Handbook Annals of Applied Statistics 5(3) 2231-2263.
Hofmann M, Bezrukov I, Mantlik F, Aschoff P, Steinke F, Beyer T, Pichler BJ und Schölkopf B (September-2011) MRI-Based Attenuation Correction for Whole-Body PET/MRI: Quantitative Evaluation of Segmentation- and Atlas-Based Methods Journal of Nuclear Medicine 52(9) 1392-1399.
Schölkopf B (Juli-2011) Empirical Inference International Journal of Materials Research 2011(7) 809-814.
Hirsch M, Harmeling S, Sra S und Schölkopf B (Juli-2011) Online Multi-frame Blind Deconvolution with Super-resolution and Saturation Correction Astronomy & Astrophysics 531(A9) 11 pages.
Gomez Rodriguez M, Peters J, Hill J, Schölkopf B, Gharabaghi A und Grosse-Wentrup M (Juni-2011) Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery Journal of Neural Engineering 8(3) 1-12.
Grosse-Wentrup M, Schölkopf B und Hill J (Mai-2011) Causal Influence of Gamma Oscillations on the Sensorimotor Rhythm NeuroImage 56(2) 837-842.
Mantlik F, Hofmann M, Werner MK, Sauter A, Kupferschläger J, Schölkopf B, Pichler BJ und Beyer T (Mai-2011) The effect of patient positioning aids on PET quantification in PET/MR imaging European Journal of Nuclear Medicine and Molecular Imaging 38(5) 920-929.
Ramos Murguialday A, Hill J, Bensch M, Martens S, Halder S, Nijboer F, Schölkopf B, Birbaumer N und Gharabaghi A (Mai-2011) Transition from the locked in to the completely locked-in state: A physiological analysis Clinical Neurophysiology 122(5) 925-933.
Kam-Thong T, Czamara D, Tsuda K, Borgwardt K, Lewis CM, Erhardt-Lehmann A, Hemmer B, Rieckmann P, Daake M, Weber F, Wolf C, Ziegler A, Pütz B, Holsboer F, Schölkopf B und Müller-Myhsok B (April-2011) EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units European Journal of Human Genetics 19(4) 465-471.
Hirsch M, Schölkopf B und Habeck M (März-2011) A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps Journal of Computational Biology 18(3) 335-346.
Georgii E, Tsuda K und Schölkopf B (Februar-2011) Multi-way set enumeration in weight tensors Machine Learning 82(2) 123-155.
Martens SMM, Mooij JM, Hill NJ, Farquhar J und Schölkopf B (Januar-2011) A graphical model framework for decoding in the visual ERP-based BCI speller Neural Computation 23(1) 160-182.
Besserve M, Schölkopf B, Logothetis NK und Panzeri S (Dezember-2010) Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis Journal of Computational Neuroscience 29(3) 547-566.
Janzing D und Schölkopf B (Oktober-2010) Causal Inference Using the Algorithmic Markov Condition IEEE Transactions on Information Theory 56(10) 5168-5194.
Steinke F, Hein M und Schölkopf B (September-2010) Nonparametric Regression between General Riemannian Manifolds SIAM Journal on Imaging Sciences 3(3) 527-563.
Camps-Valls G, Mooij JM und Schölkopf B (Juli-2010) Remote Sensing Feature Selection by Kernel Dependence Estimation IEEE Geoscience and Remote Sensing Letters 7(3) 587-591.
Bridle S, Balan ST, Bethge M, Gentile M, Harmeling S, Heymans C, Hirsch M, Hosseini R, Jarvis M, Kirk D, Kitching T, Kuijken K, Lewis A, Paulin-Henriksson S, Schölkopf B, Velander M, Voigt L, Witherick D, Amara A, Bernstein G, Courbin F, Gill M, Heavens A, Mandelbaum R, Massey R, Moghaddam B, Rassat A, Refregier A, Rhodes J, Schrabback T, Shawe-Taylor J, Shmakova M, van Waerbeke L und Wittman D (Juli-2010) Results of the GREAT08 Challenge: An image analysis competition for cosmological lensing Monthly Notices of the Royal Astronomical Society 405(3) 2044-2061.
Sriperumbudur BK, Gretton A, Fukumizu K, Schölkopf B und Lanckriet GRG (April-2010) Hilbert Space Embeddings and Metrics on Probability Measures Journal of Machine Learning Research 11 1517-1561.
Seeger M, Nickisch H, Pohmann R und Schölkopf B (Januar-2010) Optimization of k-Space Trajectories for Compressed Sensing by Bayesian Experimental Design Magnetic Resonance in Medicine 63(1) 116-126.
Jäkel F, Schölkopf B und Wichmann FA (September-2009) Does Cognitive Science Need Kernels? Trends in Cognitive Sciences 13(9) 381-388.
Corfield D, Schölkopf B und Vapnik V (Juli-2009) Falsificationism and Statistical Learning Theory: Comparing the Popper and Vapnik-Chervonenkis Dimensions Journal for General Philosophy of Science 40(1) 51-58.
Kienzle W, Franz MO, Schölkopf B und Wichmann FA (Mai-2009) Center-surround patterns emerge as optimal predictors for human saccade targets Journal of Vision 9(5:7) 1-15.
Martens SMM, Hill NJ, Farquhar J und Schölkopf B (April-2009) Overlap and refractory effects in a Brain-Computer Interface speller based on the visual P300 Event-Related Potential Journal of Neural Engineering 6(2) 1-9.
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Last updated: Montag, 22.05.2017