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Seminar Advanced Deep Learning

Lecturers

Details

Time and place:

  • Mon 8:15-9:45

Fields of study

  • WPF INF-MA from SEM 1
  • WPF MT-MA-BDV from SEM 1
  • WPF CE-MA-TA-MT from SEM 1

Prerequisites / Organizational information

Registration via StudOn:
https://www.studon.fau.de/crs4006742.html

Content

Deep Learning-based algorithms showed great performance in many fields of image processing and pattern recognition and compete with technologies such as compressive sensing and iterative optimization. The basis for the success of these algorithms is the availability of large amounts of data (big data) for training and of high computing power (typically GPUs).
In this seminar we try to explore advanced deep learning methods. In particular, we will aim to develop a deeper understanding of certain topics, for example: graph neural networks, unsupervised learning, differentiable learning, invertible learning, neural ordinary differential equations, transfer learning, multi-task learning, uncertainty DL, etc.

Additional information

Keywords: algorithms; medical image processing

Expected participants: 10