Harmeling, S., Hirsch, M., Sra, S., Schölkopf, B., Schuler, C.
Method and device for recovering a digital image from a sequence of observed digital images
European Patent, No. 11767924.1, November 2015 (patent)
Grimm, Dominik
easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies
Eberhard Karls Universität Tübingen, November 2015 (phdthesis)
Sgouritsa, E.
Causal Discovery Beyond Conditional Independences
Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)
Muandet, K.
From Points to Probability Measures: A Statistical Learning on Distributions with Kernel Mean Embedding
University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)
Schuler, C.
Machine Learning Approaches to Image Deconvolution
University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)
Charpiat, G., Hofmann, M., Schölkopf, B.
Kernel methods in medical imaging
In Handbook of Biomedical Imaging, pages: 63-81, 4, (Editors: Paragios, N., Duncan, J. and Ayache, N.), Springer, Berlin, Germany, June 2015 (inbook)
Loktyushin, A.
Blind Retrospective Motion Correction of MR Images
University of Tübingen, Germany, May 2015 (phdthesis)
O’Donnell, L. J., Schultz, T.
Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Diffusion Imaging Data
In Visualization and Processing of Higher Order Descriptors for Multi-Valued Data, pages: 299-319, (Editors: Hotz, I. and Schultz, T.), Springer, 2015 (inbook)
Hohmann, M.
A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)
Gao, M.
Sequential Image Deconvolution Using Probabilistic Linear Algebra
Technical University of Munich, Germany, 2015 (mastersthesis)
Casarsa de Azevedo, L.
Causal Inference in Neuroimaging
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)
Ibarra Chaoul, A.
The effect of frowning on attention
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)
Janzing, D., Steudel, B., Shajarisales, N., Schölkopf, B.
Justifying Information-Geometric Causal Inference
In Measures of Complexity: Festschrift for Alexey Chervonenkis, pages: 253-265, 18, (Editors: Vovk, V., Papadopoulos, H. and Gammerman, A.), Springer, 2015 (inbook)
Kuss, M.
Nonlinear Multivariate Analysis with Geodesic Kernels
Biologische Kybernetik, Technische Universität Berlin, February 2002 (diplomathesis)
Bousquet, O.
Concentration Inequalities and Empirical Processes Theory Applied to the Analysis of Learning Algorithms
Biologische Kybernetik, Ecole Polytechnique, 2002 (phdthesis) Accepted
Chapelle, O.
Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge
Biologische Kybernetik, 2002 (phdthesis)
Eichhorn, J.
Variationsverfahren zur Untersuchung von
Grundzustandseigenschaften des Ein-Band Hubbard-Modells
Biologische Kybernetik, Technische Universität Dresden, Dresden/Germany, May 2001 (diplomathesis)
Peters, J.
Cerebellar Control of Robot Arms
Biologische Kybernetik, Technische Univeristät München, München, Germany, 2001 (diplomathesis)
Seldin, Y.
On Unsupervised Learning of Mixtures of Markov Sources
Biologische Kybernetik, The Hebrew University of Jerusalem, Israel, 2001 (diplomathesis)
Dahmen, H-J., Franz, MO., Krapp, HG.
Extracting egomotion from optic flow: limits of accuracy and neural matched filters
In pages: 143-168, Springer, Berlin, 2001 (inbook)
Lal, TN.
Support Vector Machines: Theorie und Anwendung auf Prädiktion epileptischer Anfälle auf der Basis von EEG-Daten
Biologische Kybernetik, Institut für Angewandte Mathematik, Universität Bonn, 2001, Advised by Prof. Dr. S. Albeverio (diplomathesis)
Rätsch, G., Schölkopf, B., Smola, A., Mika, S., Onoda, T., Müller, K.
Robust ensemble learning
In Advances in Large Margin Classifiers, pages: 207-220, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D. Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)
Smola, A., Elisseeff, A., Schölkopf, B., Williamson, R.
Entropy numbers for convex combinations and MLPs
In Advances in Large Margin Classifiers, pages: 369-387, Neural Information Processing Series, (Editors: AJ Smola and PL Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA,, October 2000 (inbook)
Oliver, N., Schölkopf, B., Smola, A.
Natural Regularization from Generative Models
In Advances in Large Margin Classifiers, pages: 51-60, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)
Urbanek, M.
Three-dimensional reconstruction of planar scenes
Biologische Kybernetik, INP Grenoble, Warsaw University of Technology, September 2000 (diplomathesis)
Harmeling, S.
Solving Satisfiability Problems with Genetic Algorithms
In Genetic Algorithms and Genetic Programming at Stanford 2000, pages: 206-213, (Editors: Koza, J. R.), Stanford Bookstore, Stanford, CA, USA, June 2000 (inbook)
Schölkopf, B.
Statistical Learning and Kernel Methods
In CISM Courses and Lectures, International Centre for Mechanical Sciences Vol.431, CISM Courses and Lectures, International Centre for
Mechanical Sciences, 431(23):3-24, (Editors: G Della Riccia and H-J Lenz and R Kruse), Springer, Vienna, Data Fusion and Perception, 2000 (inbook)
Zhou, D.
Intelligence as a Complex System
Biologische Kybernetik, 2000 (phdthesis)
Peters, J.
Neural Networks in Robot Control
Biologische Kybernetik, Fernuniversität Hagen, Hagen, Germany, 2000 (diplomathesis)
Müller, K., Mika, S., Rätsch, G., Tsuda, K., Schölkopf, B.
An Introduction to Kernel-Based Learning Algorithms
In Handbook of Neural Network Signal Processing, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (inbook)
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