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

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

Follow Us

Publications - page 3

Generative Aging of Brain MR-Images and Prediction of Alzheimer Progression

Viktor Wegmayr, Maurice Hörold, Joachim M. Buhmann,

41st DAGM German Conference on Pattern Recognition (DAGM GCPR 2019), 11824

Research Collection

Generative Aging Of Brain MRI For Early Prediction Of MCI-AD Conversion

Viktor Wegmayr, Maurice Hörold, Joachim M. Buhmann,

16th IEEE International Symposium on Biomedical Imaging (ISBI),

Research Collection

Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs

Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann,

22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), 89

DOI: 10.3929/ethz-b-000385688      Research Collection

Exact Recovery for a Family of Community-Detection Generative Models

Luca Corinzia, Paolo Penna, Luca Mondada, Joachim M. Buhmann,

IEEE International Symposium on Information Theory (ISIT 2019),

Research Collection

Entrack: A Data-Driven Maximum-Entropy Approach to Fiber Tractography

Viktor Wegmayr, Giacomo Giuliari, Joachim M. Buhmann,

41st DAGM German Conference on Pattern Recognition (DAGM GCPR 2019), 11824

Research Collection

Disentangled state space models: Unsupervised learning of dynamics across heterogeneous environments

Đorđe Miladinović, Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer,

Deep Generative Models for Highly Structured Data (ICLR 2019 Workshop),

Research Collection

Wheel Defect Detection With Machine Learning

Gabriel Krummenacher, Cheng S. Ong, Stefan Koller, Seijin Kobayashi, Joachim M. Buhmann,

IEEE Transactions on Intelligent Transportation Systems, 19

Research Collection

Validity of GRE General Test scores and TOEFL scores for graduate admission to a technical university in Western Europe

Judith Zimmermann, Alina A. von Davier, Joachim M. Buhmann, Hans R. Heinimann,

European Journal of Engineering Education, 43

Research Collection

Semiautomatic Assessment of the Terminal Ileum and Colon in Patients with Crohn Disease Using MRI (the VIGOR++ Project)

Carl A.J. Puylaert, Peter J. Schüffler, Robiel E. Naziroglu, Jeroen A.W. Tielbeek, Li Zhang, Jesica C. Makanyanga, Charlotte J. Tutein Nolthenius, C. Yung Nio, Doug A. Pendsé, Alex Menys, Cyriel Y. Ponsioen, David Atkinson, Alastair Forbes, Joachim M. Buhmann, Thomas J. Fuchs, Haralambos Hatzakis, Lucas J. van Vliet, Jaap Stoker, Stuart A. Taylor, Frans M. Vos,

Academic Radiology, 25

Research Collection

Scalable variational inference for dynamical systems

Nico S. Gorbach, Stefan Bauer, Joachim M. Buhmann,

31st Annual Conference on Neural Information Processing Systems (NIPS 2017), 7

Research Collection