69 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)

**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)

**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)

**Camera-specific Image Denoising**
Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

**Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI**
Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience},
year = {2013},
month = {7},
volume = {14},
number = {Supplement 1},
pages = {A1}, (talk)

**Modelling and Learning Approaches to Image Denoising**
Eberhard Karls Universität Tübingen, Germany, 2013 (phdthesis)

**MR-Based Attenuation Correction for Combined Brain PET/MR: Robustness of Atlas- and Pattern Recognition Method to Atlas Registration Failures**
IEEE Nuclear Science Symposium and Medical Imaging Conference (IEEE MIC), 2013 (talk)

**Proceedings of the 10th European Workshop on Reinforcement Learning, Volume 24 **
pages: 173, JMLR, European Workshop On Reinforcement Learning, EWRL, 2013 (proceedings)

**Domain Generalization via Invariant Feature Representation**
30th International Conference on Machine Learning (ICML2013), 2013 (talk)

**Linear mixed models for genome-wide association studies**
University of Tübingen, Germany, 2013 (phdthesis)

**Modeling and Learning Complex Motor Tasks: A case study on Robot Table Tennis**
Technical University Darmstadt, Germany, 2013 (phdthesis)

**Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik**
Springer, 2013 (book)

**Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Models**
Technical University Darmstadt, Germany, 2013 (phdthesis)

**Spectral clustering and transductive inference for graph data**
NIPS Workshop on Kernel Methods and Structured Domains, December 2005 (talk)

**Some thoughts about Gaussian Processes**
NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)

Chapelle, O.
**A taxonomy of semi-supervised learning algorithms**
Yahoo!, December 2005 (talk)

**Extension to Kernel Dependency Estimation with Applications to Robotics**
Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

**Geometrical aspects of statistical learning theory**
Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

**Implicit Surfaces For Modelling
Human Heads**
Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

**Machine Learning Methods for Brain-Computer Interdaces**
Biologische Kybernetik, University of Darmstadt, September 2005 (phdthesis)

**Building Sparse Large Margin Classifiers**
The 22nd International Conference on Machine Learning (ICML), August 2005 (talk)

**Learning from Labeled and Unlabeled Data on a Directed Graph**
The 22nd International Conference on Machine Learning, August 2005 (talk)

**Liver Perfusion using Level Set Methods**
Biologische Kybernetik, Shanghai JiaoTong University, Shanghai, China, July 2005 (diplomathesis)

**Machine-Learning Approaches to BCI in Tübingen**
Brain-Computer Interface Technology, June 2005, Talk given by NJH. (talk)

**Learning Motor Primitives with Reinforcement Learning**
ROBOTICS Workshop on Modular Foundations for Control and Perception, June 2005 (talk)

**Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain**
Biologische Kybernetik, Eberhard-Karls University Tübingen, Tübingen, Germany, May 2005 (diplomathesis)

**Discriminative Methods for Label Sequence Learning**
Brown University, Providence, RI, USA, May 2005 (phdthesis)

**Support Vector Classification of Images with Local Features**
Biologische Kybernetik, University of Massachusetts, Amherst, May 2005 (diplomathesis)

**Motor Skill Learning for Humanoid Robots**
First Conference Undergraduate Computer Sciences and Informations Sciences (CS/IS), May 2005 (talk)

**Efficient Pattern Selection for Support Vector Classifiers and its CRM Application**
Biologische Kybernetik, Seoul National University, Seoul, Korea, February 2005 (phdthesis)

**Kernel Constrained Covariance for Dependence Measurement**
AISTATS, January 2005 (talk)

**Kernels: Regularization and Optimization**
Biologische Kybernetik, The Australian National University, Canberra, Australia, 2005 (phdthesis)

Zhou, D.
**How to learn from very few examples?**
October 2004 (talk)

Zhou, D.
**Discrete vs. Continuous: Two Sides of Machine Learning**
October 2004 (talk)

Zhou, D.
**Discrete vs. Continuous: Two Sides of Machine Learning**
October 2004 (talk)

**Independent component analysis and beyond**
Biologische Kybernetik, Universität Potsdam, Potsdam, October 2004 (phdthesis)

**Grundlagen von Support Vector Maschinen und Anwendungen in der Bildverarbeitung**
September 2004 (talk)

**Advanced Lectures on Machine Learning**
*ML Summer Schools 2003*, LNAI 3176, pages: 240, Springer, Berlin, Germany, ML Summer Schools, September 2004 (proceedings)

**Pattern Recognition: 26th DAGM Symposium, LNCS, Vol. 3175**
*Proceedings of the 26th Pattern Recognition Symposium (DAGM‘04)*, pages: 581, Springer, Berlin, Germany, 26th Pattern Recognition Symposium, August 2004 (proceedings)

**Kernel Methods in Computational Biology**
pages: 410, Computational Molecular Biology, MIT Press, Cambridge, MA, USA, August 2004 (book)

**The benefit of liquid Helium cooling for Cryo-Electron Tomography: A quantitative
comparative study**
The thirteenth European Microscopy Congress, August 2004 (talk)