37 results
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**Elements of Causal Inference - Foundations and Learning Algorithms**
Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

**Robot Learning**
In *Springer Handbook of Robotics*, pages: 357-394, 15, 2nd, (Editors: Siciliano, Bruno and Khatib, Oussama), Springer International Publishing, 2017 (inbook)

**Nonparametric Disturbance Correction and Nonlinear Dual Control**
(24098), ETH Zurich, 2017 (phdthesis)

**Policy Gradient Methods**
In *Encyclopedia of Machine Learning and Data Mining*, pages: 982-985, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

**Unsupervised clustering of EOG as a viable substitute for optical eye-tracking**
In *First Workshop on Eye Tracking and Visualization (ETVIS 2015)*, pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

**New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481)**
*Dagstuhl Reports*, 6(11):142-167, 2017 (book)

**Statistical Asymmetries Between Cause and Effect**
In *Time in Physics*, pages: 129-139, Tutorials, Schools, and Workshops in the Mathematical Sciences, (Editors: Renner, Renato and Stupar, Sandra), Springer International Publishing, Cham, 2017 (inbook)

**Robot Learning**
In *Encyclopedia of Machine Learning and Data Mining*, pages: 1106-1109, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

**Development and Evaluation of a Portable BCI System for Remote Data Acquisition**
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

**Brain-Computer Interfaces for patients with Amyotrophic Lateral Sclerosis**
Eberhard Karls Universität Tübingen, Germany, 2017 (phdthesis)

**Causal models for decision making via integrative inference**
University of Stuttgart, Germany, 2017 (phdthesis)

**Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation**
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

**Scalable graph kernels**
Eberhard Karls Universität Tübingen, Germany, October 2012 (phdthesis)

**Learning Motor Skills: From Algorithms to Robot Experiments**
Technische Universität Darmstadt, Germany, March 2012 (phdthesis)

**Expectation-Maximization methods for solving (PO)MDPs and optimal control problems**
In *Inference and Learning in Dynamic Models*, (Editors: Barber, D., Cemgil, A.T. and Chiappa, S.), Cambridge University Press, Cambridge, UK, January 2012 (inbook) In press

**Inferential structure determination from NMR data**
In *Bayesian methods in structural bioinformatics*, pages: 287-312, (Editors: Hamelryck, T., Mardia, K. V. and Ferkinghoff-Borg, J.), Springer, New York, 2012 (inbook)

**Structure and Dynamics of Diffusion Networks**
Department of Electrical Engineering, Stanford University, 2012 (phdthesis)

**Robot Learning**
In *Encyclopedia of the sciences of learning*, (Editors: Seel, N.M.), Springer, Berlin, Germany, 2012 (inbook)

**Reinforcement Learning in Robotics: A Survey**
In *Reinforcement Learning*, 12, pages: 579-610, (Editors: Wiering, M. and Otterlo, M.), Springer, Berlin, Germany, 2012 (inbook)

**Blind Deconvolution in Scientific Imaging & Computational Photography**
Eberhard Karls Universität Tübingen, Germany, 2012 (phdthesis)

**Restricted structural equation models for causal inference**
ETH Zurich, Switzerland, 2012 (phdthesis)

**Higher-Order Tensors in Diffusion MRI**
In *Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data*, (Editors: Westin, C. F., Vilanova, A. and Burgeth, B.), Springer, 2012 (inbook) Accepted

**Combinatorial Problems with Submodular Coupling in Machine Learning and Computer Vision**
ETH Zürich, Switzerland, 2012 (phdthesis)

**Automatische Seitenkettenzuordnung zur NMR Proteinstrukturaufklärung mittels ganzzahliger linearer Programmierung**
University of Tübingen, Germany, 2012 (diplomathesis)

**Nonparametric System Identification and Control for Periodic Error Correction in Telescopes**
University of Stuttgart, 2012 (diplomathesis)

**Reinforcement Learning for Motor Primitives**
Biologische Kybernetik, University of Stuttgart, Stuttgart, Germany, August 2008 (diplomathesis)

**Asymmetries of Time Series under Inverting their Direction**
Biologische Kybernetik, University of Heidelberg, August 2008 (diplomathesis)

**Learning an Interest Operator from Human Eye Movements**
Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, July 2008 (phdthesis)

**New Frontiers in Characterizing Structure and Dynamics by NMR**
In *Computational Structural Biology: Methods and Applications*, pages: 655-680, (Editors: Schwede, T. , M. C. Peitsch), World Scientific, New Jersey, NJ, USA, May 2008 (inbook)

**Causal inference from statistical data**
Biologische Kybernetik, Technische Hochschule Karlsruhe, Karlsruhe, Germany, April 2008 (phdthesis)

**Pairwise Correlations and Multineuronal Firing Patterns in
Primary Visual Cortex**
Biologische Kybernetik, Eberhard Karls Universität Tübingen, Tübingen, Germany, April 2008 (diplomathesis)

**Development and Application of a Python Scripting Framework for BCI2000**
Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, January 2008 (diplomathesis)

**Efficient and Invariant Regularisation with Application to Computer Graphics**
Biologische Kybernetik, University of Queensland, Brisbane, Australia, January 2008 (phdthesis)

**A Robot System for Biomimetic Navigation: From Snapshots to Metric Embeddings of View Graphs**
In *Robotics and Cognitive Approaches to Spatial Mapping*, pages: 297-314, Springer Tracts in Advanced Robotics ; 38, (Editors: Jefferies, M.E. , W.-K. Yeap), Springer, Berlin, Germany, 2008 (inbook)

**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)

**Advances in Large Margin Classifiers**
pages: 422, Neural Information Processing, MIT Press, Cambridge, MA, USA, October 2000 (book)

**An Introduction to Kernel-Based Learning Algorithms**
In *Handbook of Neural Network Signal Processing*, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (inbook)