Project Representation Learning


  • Bernhard Kainz


Time and place:

  • Time and place on appointment

Fields of study

  • WPF AI-MA from SEM 1
  • WPF MT-MA from SEM 1
  • WPF INF-MA from SEM 1

Prerequisites / Organizational information

Deep Learning ML Prof. Dr. Andreas Maier 2+2 5 x E
Pattern Recognition ML Prof. Dr. Andreas Maier 3+1+2 5 x E
Maschinelles Lernen für Zeitreihen ML Prof. Eskofier, Prof. Oliver Amft, Dr. Ch. Mutschler 2+2+2 7.5 x E


Different projects in the area of (deep) representation learning are on offer. These reach from theoretical exploration of new data representation methods to practical evaluation of applications in, e.g., medical image analysis.
Example projects will be made available on the website of the chair for health data science. Students may also propose their own projects, which will be coordinated and refined with the module lead during preliminary discussions.

Recommended Literature

A specific reading list will be established at the beginning of each project, general literature is listed below: Quinn J, McEachen J, Fullan M, Gardner M, Drummy M. Dive into deep learning: Tools for engagement. Corwin Press; 2019 Jul 15. Goodfellow I, Bengio Y, Courville A, Bengio Y. Deep learning. Cambridge: MIT press; 2016 Nov 18.

Additional information

Expected participants: 10