64 results
(View BibTeX file of all listed publications)

**A virtual reality environment for experiments in assistive robotics and neural interfaces**
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

**Optimal Trajectory Generation and Learning Control for Robot Table Tennis**
Technical University Darmstadt, Germany, 2018 (phdthesis)

**On the Applicability of Machine Learning to Aid the Search for Gravitational Waves at the LIGO Experiment**
Karlsruhe Institute of Technology, Germany, 2018 (mastersthesis)

**Distribution-Dissimilarities in Machine Learning**
Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

**Maschinelles Lernen: Entwicklung ohne Grenzen?**
In *Mit Optimismus in die Zukunft schauen. Künstliche Intelligenz - Chancen und Rahmenbedingungen*, pages: 26-34, (Editors: Bender, G. and Herbrich, R. and Siebenhaar, K.), B&S Siebenhaar Verlag, 2018 (incollection)

**Domain Adaptation Under Causal Assumptions**
Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

Suter, R.
**A Causal Perspective on Deep Representation Learning**
ETH Zurich, 2018 (mastersthesis)

**Probabilistic Approaches to Stochastic Optimization**
Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

**Improving Tissue Differentiation based on Optical Emission Spectroscopy for Guided Electrosurgical Tumor Resection with Machine Learning**
Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

**Reinforcement Learning for High-Speed Robotics with Muscular Actuation**
Ruprecht-Karls-Universität Heidelberg , 2018 (mastersthesis)

**Methods in Psychophysics**
In *Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience*, 5 (Methodology), 7, 4th, John Wiley & Sons, Inc., 2018 (inbook)

**Transfer Learning for BCIs**
In *Brain–Computer Interfaces Handbook*, pages: 425-442, 22, (Editors: Chang S. Nam, Anton Nijholt and Fabien Lotte), CRC Press, 2018 (incollection)

**Probabilistic Ordinary Differential Equation Solvers — Theory and Applications**
Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

** A machine learning approach to taking EEG-based computer interfaces out of the lab**
Graduate Training Centre of Neuroscience, IMPRS, Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

**Nonlinear functional causal models for distinguishing cause from effect**
In *Statistics and Causality: Methods for Applied Empirical Research*, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)

**A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis**
In *Brain-Computer Interfaces: Lab Experiments to Real-World Applications*, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)

**Tractable Structured Prediction using the Permutohedral Lattice**
ETH Zurich, 2016 (phdthesis)

**Advances in computational imaging: Benchmarking Deblurring Algorithms, Deep Neural Inpainting, Depth Estimation from Light Fields**
Eberhard Karls Universität Tübingen, Germany, 2016 (phdthesis)

**Screening Rules for Convex Problems**
2016 (unpublished) Submitted

**Markerless tracking of Dynamic 3D Scans of Faces**
In *Dynamic Faces: Insights from Experiments and Computation*, pages: 255-276, (Editors: Curio, C., Bülthoff, H. H. and Giese, M. A.), MIT Press, Cambridge, MA, USA, December 2010 (inbook)

**Policy Gradient Methods**
In *Encyclopedia of Machine Learning*, pages: 774-776, (Editors: Sammut, C. and Webb, G. I.), Springer, Berlin, Germany, December 2010 (inbook)

**Approximate Inference in Graphical Models**
University of Cambridge, November 2010 (phdthesis)

**Bayesian Inference and Experimental Design for Large Generalised Linear Models**
Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

**Inferring High-Dimensional Causal Relations using Free Probability Theory**
Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)

**Predictive Representations For Sequential Decision Making Under Uncertainty**
Université Laval, Quebec, Canada, July 2010 (phdthesis)

**Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data**
Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 (diplomathesis)

**Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET)**
Biologische Kybernetik, Universität Mannheim, Germany, March 2010 (diplomathesis)

**Learning Continuous Grasp Affordances by Sensorimotor Exploration**
In *From Motor Learning to Interaction Learning in Robots*, pages: 451-465, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling**
In *From Motor Learning to Interaction Learning in Robots*, pages: 209-225, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**From Motor Learning to Interaction Learning in Robots**
In *From Motor Learning to Interaction Learning in Robots*, pages: 1-12, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**From Motor Learning to Interaction Learning in Robots**
pages: 538, Studies in Computational Intelligence ; 264, (Editors: O Sigaud, J Peters), Springer, Berlin, Germany, January 2010 (book)

**Real-Time Local GP Model Learning**
In *From Motor Learning to Interaction Learning in Robots*, 264, pages: 193-207, Studies in Computational Intelligence, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**Machine Learning Methods for Automatic Image Colorization**
In *Computational Photography: Methods and Applications*, pages: 395-418, Digital Imaging and Computer Vision, (Editors: Lukac, R.), CRC Press, Boca Raton, FL, USA, 2010 (inbook)

**Finding Gene-Gene Interactions using Support Vector Machines**
Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

**Accurate Prediction of Protein-Coding Genes with Discriminative Learning Techniques**
Technische Universität Berlin, Germany, 2010 (phdthesis)

**Quantitative Positron Emission Tomography with a Combined PET/MR System**
University of Oxford, UK, 2010 (phdthesis)

**Structural and Relational Data Mining for Systems Biology Applications**
Eberhard Karls Universität Tübingen, Germany , 2010 (phdthesis)

**Population Coding in the Visual System: Statistical Methods and Theory**
Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

**Bayesian Methods for Neural Data Analysis**
Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

**Clustering with Neighborhood Graphs**
Universität des Saarlandes, Saarbrücken, Germany, 2010 (phdthesis)

**Approaches Based on Support Vector Machine to Classification of Remote Sensing Data**
In *Handbook of Pattern Recognition and Computer Vision*, pages: 329-352, (Editors: Chen, C.H.), ICP, London, UK, 2010 (inbook)

**Detecting and modeling time shifts in microarray time series data applying Gaussian processes**
Eberhard Karls Universität Tübingen, Germany, 2010 (thesis)

**Detecting the mincut in sparse random graphs
**
Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

**A wider view on encoding and decoding in the visual brain-computer interface speller system**
Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

**Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond**
pages: 644, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, USA, December 2002, Parts of this book, including an introduction to kernel methods, can be downloaded here. (book)

**Nonlinear Multivariate Analysis with Geodesic Kernels**
Biologische Kybernetik, Technische Universität Berlin, February 2002 (diplomathesis)

**Concentration Inequalities and Empirical Processes Theory Applied to the Analysis of Learning Algorithms**
Biologische Kybernetik, Ecole Polytechnique, 2002 (phdthesis) Accepted

**Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge**
Biologische Kybernetik, 2002 (phdthesis)

**Variationsverfahren zur Untersuchung von
Grundzustandseigenschaften des Ein-Band Hubbard-Modells**
Biologische Kybernetik, Technische Universität Dresden, Dresden/Germany, May 2001 (diplomathesis)

**Cerebellar Control of Robot Arms**
Biologische Kybernetik, Technische Univeristät München, München, Germany, 2001 (diplomathesis)