62 results
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**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)

**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)

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

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

**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)

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