26 results
(View BibTeX file of all listed publications)

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

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

**From Optimal Transport to Generative Modeling: the VEGAN cookbook**
2017 (techreport)

**Frequent Subgraph Retrieval in Geometric Graph Databases**
(180), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2008 (techreport)

**Simultaneous Implicit Surface
Reconstruction and Meshing**
(179), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2008 (techreport)

**Taxonomy Inference Using Kernel Dependence
Measures**
(181), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2008 (techreport)

**Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models**
(175), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2008 (techreport)

**Block-Iterative Algorithms for
Non-Negative Matrix Approximation**
(176), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2008 (techreport)

**Approximation Algorithms for Bregman
Clustering Co-clustering and Tensor Clustering**
(177), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2008 (techreport)

**Combining Appearance and Motion for Human
Action Classification in Videos**
(174), Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, August 2008 (techreport)

**Example-based Learning for Single-image
Super-resolution and JPEG Artifact Removal**
(173), Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, August 2008 (techreport)

**Unsupervised Bayesian Time-series Segmentation based on Linear Gaussian State-space Models**
(171), Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, June 2008 (techreport)

**A New Non-monotonic Gradient Projection Method for the Non-negative Least Squares Problem**
(TR-08-28), University of Texas, Austin, TX, USA, June 2008 (techreport)

**Non-monotonic Poisson Likelihood Maximization**
(170), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2008 (techreport)

**A Kernel Method for the Two-sample Problem**
(157), Max-Planck-Institute for Biological Cybernetics Tübingen, April 2008 (techreport)

**Energy Functionals for
Manifold-valued Mappings and
Their Properties**
(167), Max Planck Institute for Biological Cybernetics, Tübingen, January 2008 (techreport)

**Minimal Logical Constraint Covering Sets**
(155), Max Planck Institute for Biological Cybernetics, Tübingen, December 2006 (techreport)

**New Methods for the P300 Visual Speller**
(1), (Editors: Hill, J. ), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2006 (techreport)

**Geometric Analysis of Hilbert Schmidt Independence criterion based ICA contrast function**
(PA006080), National ICT Australia, Canberra, Australia, October 2006 (techreport)

**Semi-Supervised Learning**
pages: 508, Adaptive computation and machine learning, MIT Press, Cambridge, MA, USA, September 2006 (book)

**A tutorial on spectral clustering**
(149), Max Planck Institute for Biological Cybernetics, Tübingen, August 2006 (techreport)

**Towards the Inference of Graphs on Ordered Vertexes**
(150), Max Planck Institute for Biological Cybernetics, Tübingen, August 2006 (techreport)

**An Automated Combination of Sequence Motif Kernels for Predicting Protein Subcellular Localization**
(146), Max Planck Institute for Biological Cybernetics, Tübingen, April 2006 (techreport)

**Training a Support Vector Machine in the Primal**
(147), Max Planck Institute for Biological Cybernetics, Tübingen, April 2006, The version in the "Large Scale Kernel Machines" book is more up to date. (techreport)

**Cross-Validation Optimization for Structured Hessian Kernel Methods**
Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, February 2006 (techreport)

**Gaussian Processes for Machine Learning**
pages: 248, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, USA, January 2006 (book)