Contact

Prof. Dr. Bernhard Schölkopf

Address: Spemannstr. 38
72076 Tübingen
Room number: 211
Phone: +49 7071 601 551
Fax: +49 7071 601 552
E-Mail: bernhard.schoelkopf

 

Picture of Schölkopf, Bernhard, Prof. Dr.

Bernhard Schölkopf

Position: Director  Unit: 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 http://www.kernel-machines.org/. 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 Sabrina.Rehbaum@tuebingen.mpg.de.

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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Show abstracts

Articles (100):

Zien A, Rätsch G, Mika S, Schölkopf B, Lengauer T and Müller K-R (September-2000) Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites Bioinformatics 16(9) 799-807.
Schölkopf B, Smola AJ, Williamson RC and Bartlett PL (May-2000) New Support Vector Algorithms Neural Computation 12(5) 1207-1245.
Schölkopf B, Mika S, Burges CJC, Knirsch P, Müller K-R, Rätsch G and Smola AJ (September-1999) Input space versus feature space in kernel-based methods IEEE Transactions On Neural Networks 10(5) 1000-1017.
Schölkopf B, Müller K-R and Smola AJ (September-1999) Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten Informatik - Forschung und Entwicklung 14(3) 154-163.
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Franz M, Schölkopf B and Bülthoff HH (October-1998) Where did I take that snapshot? Scene-based homing by image matching Biological Cybernetics 79(3) 191-202.
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Smola AJ and Schölkopf B (September-1998) On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion Algorithmica 22(1-2) 211-231.
Schölkopf B (August-1998) The moon tilt illusion Perception 27(10) 1229-1232.
Schölkopf B, Smola AJ and Müller K-R (July-1998) Nonlinear Component Analysis as a Kernel Eigenvalue Problem Neural Computation 10(5) 1299-1319.
Hearst MA, Dumais ST, Osman E, Platt J and Schölkopf B (July-1998) Support vector machines IEEE Intelligent Systems and their Applications 13(4) 18-28.
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Smola AJ, Schölkopf B and Müller K-R (June-1998) The connection between regularization operators and support vector kernels Neural Networks 11(4) 637-649.
Franz M, Schölkopf B, Mallot HA and Bülthoff HH (March-1998) Learning view graphs for robot navigation Autonomous Robots 5(1) 111-125.
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Schölkopf B, Sung K, Burges C, Girosi F, Niyogi P, Poggio T and Vapnik V (November-1997) Comparing support vector machines with Gaussian kernels to radial basis function classifiers IEEE Transactions on Signal Processing 45(11) 2758-2765.
Schölkopf B and Mallot HA (January-1995) View-Based Cognitive Mapping and Path Planning Adaptive Behavior 3(3) 311-348.

Conference papers (207):

Shajarisales N, Janzing D, Schölkopf B and Besserve M (June-2016) Telling Cause from Effect in Deterministic Linear Dynamical Systems, 33rd International Conference on Machine Learning (ICML 2016), 1-10. accepted
Loktyushin A, Schuler C, Scheffler K and Schölkopf B (2016) Retrospective Motion Correction of Magnitude-Input MR Images In: Machine Learning Meets Medical Imaging, , First International Workshop on Machine Learning Meets Medical Imaging (MLMMI 2015), held in conjunction with ICML 2015, IEEE, Piscataway, NJ, USA, 3-12, Series: Lecture Notes in Computer Science ; 9487.
Shajarisales N, Janzing D, Schölkopf B and Besserve M (July-2015) Telling Cause from Effect in Deterministic Linear Dynamical Systems, 32nd International Conference on Machine Learning (ICML 2015), International Machine Learning Society, Madison, WI, USA, 285–294, Series: JMLR Workshop and Conference Proceedings ; 37.
Besserve M, Logothetis NK and Schölkopf B (2014) Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators In: Advances in Neural Information Processing Systems 26, , Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS 2013), Curran, Red Hook, NY, USA, 2537-2545.
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Mülling K, Boularias A, Mohler B, Schölkopf B and Peters J (September-27-2013) Inverse Reinforcement Learning for Strategy Extraction, ECML/PKDD 2013 Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA13), 1-9.
Wang Z, Deisenroth MP, Ben Amor H, Vogt D, Schölkopf B and Peters J (July-2013) Probabilistic Modeling of Human Movements for Intention Inference In: Robotics: Science and Systems VIII, , 2012 Robotics: Science and Systems Conference, MIT Press, Cambridge, MA, USA, 433-440.
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Gomez Rodriguez M and Schölkopf B (July-2012) Influence Maximization in Continuous Time Diffusion Networks, 29th International Conference on Machine Learning (ICML 2012), International Machine Learning Society, Madison, WI, USA, 313-320.
Schölkopf B, Janzing D, Peters J, Sgouritsa E, Zhang K and Mooij J (July-2012) On causal and anticausal learning, 29th International Conference on Machine Learning (ICML 2012), International Machine Learning Society, Madison, WI, USA, 1255-1262.
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Gomez Rodriguez M and Schölkopf B (July-2012) Submodular Inference of Diffusion Networks from Multiple Trees, 29th International Conference on Machine Learning (ICML 2012), International Machine Learning Society, Madison, WI, USA, 489-496.
Mooij J, Janzing D, Schölkopf B and Heskes T (January-2012) On Causal Discovery with Cyclic Additive Noise Models In: Advances in Neural Information Processing Systems 24, , Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Curran, Red Hook, NY, USA, 639-647.
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Gehler P, Rother C, Kiefel M, Zhang L and Schölkopf B (January-2012) Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance In: Advances in Neural Information Processing Systems 24, , Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Curran, Red Hook, NY, USA, 765-773.
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Hirsch M, Schuler CJ, Harmeling S and Schölkopf B (November-2011) Fast removal of non-uniform camera shake, 13th IEEE International Conference on Computer Vision (ICCV 2011), IEEE, Piscataway, NJ, USA, 463-470.
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Schuler CJ, Hirsch M, Harmeling S and Schölkopf B (November-2011) Non-stationary correction of optical aberrations, 13th IEEE International Conference on Computer Vision (ICCV 2011), IEEE, Piscataway, NJ, USA, 659-666.
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Joubert P, Nickell S, Beck F, Habeck M, Hirsch M and Schölkopf B (September-2011) Automatic particle picking using diffusion filtering and random forest classification, International Workshop on Microscopic Image Analysis with Application in Biology (MIAAB 2011), 1-6.
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Wang Z, Lampert CH, Mülling K, Schölkopf B and Peters J (September-2011) Learning anticipation policies for robot table tennis, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), IEEE, Piscataway, NJ, USA, 332-337.
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Bocsi B, Nguyen-Tuong D, Csato L, Schölkopf B and Peters J (September-2011) Learning inverse kinematics with structured prediction, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), IEEE, Piscataway, NJ, USA, 698-703.
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Langovoy M, Habeck M and Schölkopf B (August-2011) Adaptive nonparametric detection in cryo-electron microscopy, 58th World Statistics Congress of the International Statistical Institute (ISI 2011), 1-6.
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Langovoy M, Habeck M and Schölkopf B (August-2011) Spatial statistics, image analysis and percolation theory, 2011 Joint Statistical Meetings (JSM), American Statistical Association, Alexandria, VA, USA, 1-11.
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Achlioptas P, Schölkopf B and Borgwardt K (August-2011) Two-locus association mapping in subquadratic time, 17th ACM SIGKKD Conference on Knowledge Discovery and Data Mining (KDD 2011), ACM Press, New York, NY, USA, 726-734.
Janzing D, Sgouritsa E, Stegle O, Peters J and Schölkopf B (July-2011) Detecting low-complexity unobserved causes, 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI Press, Corvallis, OR, USA, 383-391.
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Peters J, Mooij J, Janzing D and Schölkopf B (July-2011) Identifiability of causal graphs using functional models, 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI Press, Corvallis, OR, USA, 589-598.
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Zhang K, Peters J, Janzing D and Schölkopf B (July-2011) Kernel-based Conditional Independence Test and Application in Causal Discovery, 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI Press, Corvallis, OR, USA, 804-813.
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Franc V, Zien A and Schölkopf B (July-2011) Support Vector Machines as Probabilistic Models, 28th International Conference on Machine Learning (ICML 2011), International Machine Learning Society, Madison, WI, USA, 665-672.
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Gomez Rodriguez M, Grosse-Wentrup M, Hill J, Gharabaghi A, Schölkopf B and Peters J (July-2011) Towards Brain-Robot Interfaces in Stroke Rehabilitation, 12th International Conference on Rehabilitation Robotics (ICORR 2011), IEEE, Piscataway, NJ, USA, 1-6.
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Gomez Rodriguez M, Balduzzi D and Schölkopf B (July-2011) Uncovering the Temporal Dynamics of Diffusion Networks, 28th International Conference on Machine Learning (ICML 2011), International Machine Learning Society, Madison, WI, USA, 561-568.
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Mooij JM, Stegle O, Janzing D, Zhang K and Schölkopf B (June-2011) Probabilistic latent variable models for distinguishing between cause and effect In: Advances in Neural Information Processing Systems 23, , Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Curran, Red Hook, NY, USA, 1687-1695.
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Harmeling S, Hirsch M and Schölkopf B (June-2011) Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake In: Advances in Neural Information Processing Systems 23, , Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Curran, Red Hook, NY, USA, 829-837.
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Alvarez MA, Peters J, Schölkopf B and Lawrence ND (June-2011) Switched Latent Force Models for Movement Segmentation In: Advances in neural information processing systems 23, , Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Curran, Red Hook, NY, USA, 55-63.
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Besserve M, Janzing D, Logothetis NK and Schölkopf B (May-2011) Finding dependencies between frequencies with the kernel cross-spectral density, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), IEEE, Piscataway, NJ, USA, 2080-2083.
Burger HC, Schölkopf B and Harmeling S (April-2011) Removing noise from astronomical images using a pixel-specific noise model, IEEE International Conference on Computational Photography (ICCP 2011), IEEE, Piscataway, NJ, USA, 1-8.
Gomez Rodriguez M, Peters J, Hill J, Gharabaghi A, Schölkopf B and Grosse-Wentrup M (November-2010) Combining Real-Time Brain-Computer Interfacing and Robot Control for Stroke Rehabilitation, Brain-Computer Interface Workshop at SIMPAR 2010: 2nd International Conference on Simulation, Modeling, and Programming for Autonomous Robots, 59-63.
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Gomez Rodriguez M, Peters J, Hill J, Schölkopf B, Gharabaghi A and Grosse-Wentrup M (October-2010) Closing the sensorimotor loop: Haptic feedback facilitates decoding of arm movement imagery, IEEE International Conference on Systems, Man and Cybernetics (SMC 2010), IEEE, Piscataway, NJ, USA, 121-126.
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Harmeling S, Sra S, Hirsch M and Schölkopf B (September-2010) Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction via Incremental EM, 17th International Conference on Image Processing (ICIP 2010), IEEE, Piscataway, NJ, USA, 3313-3316.
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Gomez Rodriguez M, Grosse-Wentrup M, Peters J, Naros G, Hill J, Schölkopf B and Gharabaghi A (August-2010) Epidural ECoG Online Decoding of Arm Movement Intention in Hemiparesis, 1st ICPR Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging (ICPR WBD 2010), IEEE, Piscataway, NJ, USA, 36-39.
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Daniusis P, Janzing D, Mooij J, Zscheischler J, Steudel B, Zhang K and Schölkopf B (July-2010) Inferring deterministic causal relations, 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), AUAI Press, Corvallis, OR, USA, 143-150.
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Zhang K, Schölkopf B and Janzing D (July-2010) Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery, 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), AUAI Press, Corvallis, OR, USA, 717-724.
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Steudel B, Janzing D and Schölkopf B (June-2010) Causal Markov condition for submodular information measures, 23rd Annual Conference on Learning Theory (COLT 2010), Omnipress, Madison, WI, USA, 464-476.
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Last updated: Tuesday, 18.11.2014