Publications | Max Planck Institute for Intelligent Systems

2013

ei pn Schober, M. Camera-specific Image Denoising Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

Modelling and Learning Approaches to Image Denoising

Burger, HC.

Eberhard Karls Universität Tübingen, Germany, 2013 (phdthesis)

ei Burger, HC. Modelling and Learning Approaches to Image Denoising Eberhard Karls Universität Tübingen, Germany, 2013 (phdthesis)

Linear mixed models for genome-wide association studies

Lippert, C.

University of Tübingen, Germany, 2013 (phdthesis)

ei Lippert, C. 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

Mülling, K.

Technical University Darmstadt, Germany, 2013 (phdthesis)

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

Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Models

Wang, Z.

Technical University Darmstadt, Germany, 2013 (phdthesis)

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

2010

Bayesian Inference and Experimental Design for Large Generalised Linear Models

Nickisch, H.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

PDF Web [BibTex]

2010

ei Nickisch, H. Bayesian Inference and Experimental Design for Large Generalised Linear Models Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

PDF Web [BibTex]

Inferring High-Dimensional Causal Relations using Free Probability Theory

Zscheischler, J.

Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)

ei Zscheischler, J. Inferring High-Dimensional Causal Relations using Free Probability Theory Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)

Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data

Shelton, J.

Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 (diplomathesis)

ei Shelton, J. Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 (diplomathesis)

Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET)

Mantlik, F.

Biologische Kybernetik, Universität Mannheim, Germany, March 2010 (diplomathesis)

ei Mantlik, F. Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET) Biologische Kybernetik, Universität Mannheim, Germany, March 2010 (diplomathesis)

Finding Gene-Gene Interactions using Support Vector Machines

Rakitsch, B.

Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

ei Rakitsch, B. Finding Gene-Gene Interactions using Support Vector Machines Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

Accurate Prediction of Protein-Coding Genes with Discriminative Learning Techniques

Schweikert, G.

Technische Universität Berlin, Germany, 2010 (phdthesis)

ei Schweikert, G. Accurate Prediction of Protein-Coding Genes with Discriminative Learning Techniques Technische Universität Berlin, Germany, 2010 (phdthesis)

Quantitative Positron Emission Tomography with a Combined PET/MR System

Hofmann, M.

University of Oxford, UK, 2010 (phdthesis)

ei Hofmann, M. Quantitative Positron Emission Tomography with a Combined PET/MR System University of Oxford, UK, 2010 (phdthesis)

Structural and Relational Data Mining for Systems Biology Applications

Georgii, E.

Eberhard Karls Universität Tübingen, Germany , 2010 (phdthesis)

ei Georgii, E. Structural and Relational Data Mining for Systems Biology Applications Eberhard Karls Universität Tübingen, Germany , 2010 (phdthesis)

Population Coding in the Visual System: Statistical Methods and Theory

Macke, J.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

ei Macke, J. Population Coding in the Visual System: Statistical Methods and Theory Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

Bayesian Methods for Neural Data Analysis

Gerwinn, S.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

ei Gerwinn, S. Bayesian Methods for Neural Data Analysis Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

Clustering with Neighborhood Graphs

Maier, M.

Universität des Saarlandes, Saarbrücken, Germany, 2010 (phdthesis)

ei Maier, M. Clustering with Neighborhood Graphs Universität des Saarlandes, Saarbrücken, Germany, 2010 (phdthesis)

Detecting the mincut in sparse random graphs

Köhler, R.

Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

ei Köhler, R. Detecting the mincut in sparse random graphs Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

A wider view on encoding and decoding in the visual brain-computer interface speller system

Martens, S.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

ei Martens, S. A wider view on encoding and decoding in the visual brain-computer interface speller system Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

2008

Reinforcement Learning for Motor Primitives

Kober, J.

Biologische Kybernetik, University of Stuttgart, Stuttgart, Germany, August 2008 (diplomathesis)

2008

ei Kober, J. Reinforcement Learning for Motor Primitives Biologische Kybernetik, University of Stuttgart, Stuttgart, Germany, August 2008 (diplomathesis)

Asymmetries of Time Series under Inverting their Direction

Peters, J.

Biologische Kybernetik, University of Heidelberg, August 2008 (diplomathesis)

ei Peters, J. Asymmetries of Time Series under Inverting their Direction Biologische Kybernetik, University of Heidelberg, August 2008 (diplomathesis)

Learning an Interest Operator from Human Eye Movements

Kienzle, W.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, July 2008 (phdthesis)

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

Causal inference from statistical data

Sun, X.

Biologische Kybernetik, Technische Hochschule Karlsruhe, Karlsruhe, Germany, April 2008 (phdthesis)

ei Sun, X. 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

Berens, P.

Biologische Kybernetik, Eberhard Karls Universität Tübingen, Tübingen, Germany, April 2008 (diplomathesis)

ei Berens, P. 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

Schreiner, T.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, January 2008 (diplomathesis)

ei Schreiner, T. 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

Walder, CJ.

Biologische Kybernetik, University of Queensland, Brisbane, Australia, January 2008 (phdthesis)

Abstract

This thesis develops the theory and practise of reproducing kernel methods. Many functional inverse problems which arise in, for example, machine learning and computer graphics, have been treated with practical success using methods based on a reproducing kernel Hilbert space perspective. This perspective is often theoretically convenient, in that many functional analysis problems reduce to linear algebra problems in these spaces. Somewhat more complex is the case of conditionally positive definite kernels, and we provide an introduction to both cases, deriving in a particularly elementary manner some key results for the conditionally positive definite case. A common complaint of the practitioner is the long running time of these kernel based algorithms. We provide novel ways of alleviating these problems by essentially using a non-standard function basis which yields computational advantages. That said, by doing so we must also forego the aforementioned theoretical conveniences, and hence need some additional analysis which we provide in order to make the approach practicable. We demonstrate that the method leads to state of the art performance on the problem of surface reconstruction from points. We also provide some analysis of kernels invariant to transformations such as translation and dilation, and show that this indicates the value of learning algorithms which use conditionally positive definite kernels. Correspondingly, we provide a few approaches for making such algorithms practicable. We do this either by modifying the kernel, or directly solving problems with conditionally positive definite kernels, which had previously only been solved with positive definite kernels. We demonstrate the advantage of this approach, in particular by attaining state of the art classification performance with only one free parameter.

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