47 results
(View BibTeX file of all listed publications)

**Robot Learning for Muscular Robots**
Technical University Darmstadt, Germany, December 2019 (phdthesis)

**Real Time Probabilistic Models for Robot Trajectories**
Technical University Darmstadt, Germany, December 2019 (phdthesis)

**Learning Transferable Representations**
University of Cambridge, UK, 2019 (phdthesis)

**Sample-efficient deep reinforcement learning for continuous control**
University of Cambridge, UK, 2019 (phdthesis)

**Formally justified and modular Bayesian inference for probabilistic programs**
University of Cambridge, UK, 2019 (phdthesis)

**Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing**
Technical University of Munich, Germany, 2019 (mastersthesis)

**Pragmatism and Variable Transformations in Causal Modelling**
ETH Zurich, 2019 (phdthesis)

**Quantification of tumor heterogeneity using PET/MRI and machine learning**
Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)

**Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning**
University of Cambridge, UK, 2019 (phdthesis)

**easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies**
Eberhard Karls Universität Tübingen, November 2015 (phdthesis)

**Causal Discovery Beyond Conditional Independences**
Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)

**Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism**
*53rd Annual Allerton Conference on Communication, Control, and Computing*, September 2015 (talk)

**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)

**Machine Learning Approaches to Image Deconvolution**
University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

**Blind Retrospective Motion Correction of MR Images**
University of Tübingen, Germany, May 2015 (phdthesis)

**Independence of cause and mechanism in brain networks**
*DALI workshop on Networks: Processes and Causality*, April 2015 (talk)

**Information-Theoretic Implications of Classical and Quantum Causal Structures **
18th Conference on Quantum Information Processing (QIP), 2015 (talk)

**Assessment of brain tissue damage in the Sub-Acute Stroke Region by Multiparametric Imaging using [89-Zr]-Desferal-EPO-PET/MRI**
World Molecular Imaging Conference, 2015 (talk)

**A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**Early time point in vivo PET/MR is a promising biomarker for determining efficacy of a novel Db(\alphaEGFR)-scTRAIL fusion protein therapy in a colon cancer model**
World Molecular Imaging Conference, 2015 (talk)

**Sequential Image Deconvolution Using Probabilistic Linear Algebra**
Technical University of Munich, Germany, 2015 (mastersthesis)

**Causal Inference in Neuroimaging**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**The effect of frowning on attention**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**The search for single exoplanet transits in the Kepler light curves**
*IAU General Assembly*, 22, pages: 2258352, 2015 (talk)

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)

**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)

**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

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

**Eine beweistheoretische Anwendung der **
Biologische Kybernetik, Westfälische Wilhelms-Universität Münster, Münster, May 1998 (diplomathesis)

**Qualitative Modeling for Data Miner‘s Requirement**
Biologische Kybernetik, Hong-Ik University, Seoul, Korea, February 1998, Written in Korean (diplomathesis)

**Support Vector Machines for Image Classification**
Biologische Kybernetik, Ecole Normale Superieure de Lyon, 1998 (diplomathesis)

**Support Vector methods in learning and feature extraction**
*Ninth Australian Conference on Neural Networks*, pages: 72-78, (Editors: T. Downs, M. Frean and M. Gallagher), 1998 (talk)