Information Science and Engineering Lab

We perform teaching and research in machine learning strategies for the pattern analysis of various kinds of data. This comprises statistical models for clustering, graphical models for network inference and algorithmic methods to efficiently find these structures in the data.

Contact Info
CAB F 61.1
Universitaetstrasse 6,
8092 Zurich
Schweiz

+41 44 632 64 96

Learn More

Follow Us

Information Science and Engineering Lab

We perform teaching and research in machine learning strategies for the pattern analysis of various kinds of data. This comprises statistical models for clustering, graphical models for network inference and algorithmic methods to efficiently find these structures in the data.

Contact Info
CAB F 61.1
Universitaetstrasse 6,
8092 Zurich
Schweiz

+41 44 632 64 96

Learn More

Follow Us

Others - page 13

2012 Other Conference Item

Information Theoretic Model Validation for Spectral Clustering

Morteza Haghir Chehreghani, Alberto Giovanni Busetto, Joachim M. Buhmann,

IEEE International Symposium on Information Theory (ISIT 2012),

Research Collection

2012 Other Conference Item

Inference on computational models using Bayesian global optimization

E.I. Lomakina, C. Mathys, K.H. Brodersen, A. Vezhnevets, Klaas Stephan, Joachim M. Buhmann,

Human Brain Mapping 2012,

Research Collection

2012 Journal Article

Generic comparison of protein inference engines

Manfred Claassen, Lukas Reiter, Michael O. Hengartner, Joachim M. Buhmann, Ruedi Aebersold,

Molecular & Cellular Proteomics, 11

Research Collection

2012 Journal Article

Decoding the perception of pain from fMRI using multivariate pattern analysis

Kay H Brodersen, Katja Wiech, Ekaterina I. Lomakina, Chia-shu Lin, Joachim M. Buhmann, Ulrike Bingel, Markus Ploner, Klaas Stephan, Irene Tracey,

NeuroImage, 63

Research Collection

Pain Decoding Support Vector Machine Permutation Test Classification Accuracy
2012 Conference Paper

Computational modeling for assessment of IBD: To be or not to be?

Franciscus M. Vos, Jeroen A.W. Tielbeek, Robiel E. Naziroglu, Zhang Li, Peter Schüffler, Dwarikanath Mahapatra, Alexander Wiebel, C. Lavini, Joachim M. Buhmann, Hans-Christian Hege, Jaap Stoker, Lucas van Vliet,

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2012),

Research Collection

2012 Journal Article

Bayesian Mixed-Effects Inference on Classification Performance in Hierarchical Data Sets

Kay H Brodersen, Christoph Mathys, Justin Chumbley, Jean Daunizeau, Cheng S. Ong, Joachim M. Buhmann, Klaas Stephan,

Journal of Machine Learning Research, 13

Research Collection

Beta Binomial Normal Binomial Balanced Accuracy Bayesian Inference Group Studies
2012 Journal Article

Bayesian Mixed-Effects Inference on Classification Performance in Hierarchical Data Sets-2012

Kay H Brodersen, Christoph Mathys, Justin R. Chumbley, Jean Daunizeau, Cheng Soon Ong, Joachim M. Buhmann, Klaas Stephan,

Journal of Machine Learning Research, 13

Research Collection

2012 Conference Paper

Anisotropic ssTEM Image Segmentation Using Dense Correspondence across Sections

Dmitry Laptev, Alexander Vezhnevets, Sarvesh Dwivedi, Joachim M. Buhmann,

15th International Conference for Medical Image Computing and Computer-Assisted Intervention (MICCAI 2012), 7510

Research Collection

2012 Conference Paper

Active learning for semantic segmentation with expected change

Alexander Vezhnevets, Joachim M. Buhmann, Vittorio Ferrari,

IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012),

Research Collection

2012 Journal Article

A high-throughput metabolomics method to predict high concentration cytotoxicity of drugs from low concentration profiles

Stéphanie Heux, Thomas J. Fuchs, Joachim M. Buhmann, Nicola Zamboni, Uwe Sauer,

Metabolomics, 8

DOI: 10.3929/ethz-b-000048939      Research Collection

Yeast Metabolism Drug Enzyme Interaction Off Target Drug Effects Metabolomics Method Machine Learning