51 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)

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

**Analysis of multiparametric MRI using a semi-supervised random forest framework allows the detection of therapy response in ischemic stroke**
World Molecular Imaging Conference, 2016 (talk)

**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2016 (unpublished) Submitted

**Multi-view learning on multiparametric PET/MRI quantifies intratumoral heterogeneity and determines therapy efficacy**
World Molecular Imaging Conference, 2016 (talk)

**Modeling the polygenic architecture of complex traits**
Eberhard Karls Universität Tübingen, November 2014 (phdthesis)

**Learning Motor Skills: From Algorithms to Robot Experiments**
97, pages: 191, Springer Tracts in Advanced Robotics, Springer, 2014 (book)

**Computational Diffusion MRI and Brain Connectivity**
pages: 255, Mathematics and Visualization, Springer, 2014 (book)

**Unsupervised identification of neural events in local field potentials**
44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)

**A Novel Causal Inference Method for Time Series**
Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (mastersthesis)

**Quantifying statistical dependency**
Research Network on Learning Systems Summer School, 2014 (talk)

**A global analysis of extreme events and consequences for the terrestrial carbon cycle**
Diss. No. 22043, ETH Zurich, Switzerland, ETH Zurich, Switzerland, 2014 (phdthesis)

**Development of advanced methods for improving astronomical images**
Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (diplomathesis)

**The Feasibility of Causal Discovery in Complex Systems: An Examination of Climate Change Attribution and Detection**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

**Causal Discovery in the Presence of Time-Dependent Relations or Small Sample Size**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

**Using a population based Gaussian Mixture Model on fused [18]F-FDG PET and DW-MRI images accurately segments the tumor microenvironment into clinically relevant compartments capable of guiding therapy**
European Molecular Imaging Meeting, 2014 (talk)

**Causal Inference from Passive Observations**
24th Summer School University of Jyväskylā, Finland, August, 2014 (talk)

**Analysis of Distance Functions in Graphs**
University of Hamburg, Germany, University of Hamburg, Germany, 2014 (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)

**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)

**Exploration of combining Echo-State Network Learning with Recurrent Neural Network Learning techniques**
Biologische Kybernetik, International University Bremen, Bremen, Germany, May 2004 (diplomathesis)

**Computational Analysis of Gene Expression Data**
(4), Biologische Kybernetik, March 2004 (phdthesis)

Bousquet, O.
**Introduction to Category Theory**
Internal Seminar, January 2004 (talk)

**The p53 Oligomerization Domain: Sequence-Structure Relationships and the Design and Characterization of Altered Oligomeric States**
University of Toronto, Canada, University of Toronto, Canada, 2004 (phdthesis)

**Statistical Learning with Similarity and Dissimilarity Functions**
pages: 1-166, Technische Universität Berlin, Germany, Technische Universität Berlin, Germany, 2004 (phdthesis)

**Classification and Feature Extraction in Man and Machine**
Biologische Kybernetik, University of Tübingen, Germany, 2004, online publication (phdthesis)

Bousquet, O.
**Advanced Statistical Learning Theory**
Machine Learning Summer School, 2004 (talk)

**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)

Bousquet, O.
**Transductive Learning: Motivation, Models, Algorithms**
January 2002 (talk)

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