UnivIS

Seminar Advanced Deep Learning

Dozent/in

Details

Zeit/Ort n.V.

The first session of the semester will an online meeting, subsequent meetings will be in person.

  • Di 12:00-14:00, Raum Seminarraum ZMPT (außer vac) ICS

Voraussetzungen / Organisatorisches

Registration via StudOn:
https://www.studon.fau.de/crs4006742.html
https://www.studon.uni-erlangen.de/univis_2022s.Lecture.21733718

Inhalt

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.

Zusätzliche Informationen

Schlagwörter: algorithms; medical image processing

Erwartete Teilnehmerzahl: 10