• Type: Advanced Seminar Course Module IN0014
  • Type: Master Seminar Module IN2107
  • SWS: 2+0
  • ECTS: 5 Credits
  • Location: Due to the pandemic situation, sessions will be online. Access will be shared before each session.
  • Time: TBA
  • Course Language: English


Welcome to the CAMPAR space on Graph Deep Learning for Medical Applications (GDLMA). Graph Deep Learning is a new exotic branch in many fields like computer Vision and Medical Imaging. Many real-world medical and non-medical datasets can be represented in the form of graphs, providing a powerful source of information for machine learning models. This graph-based data, combined with the success of the convolutional neural networks, has motivated to translate the key ingredients of deep learning models into the graph domain. Many communities such as healthcare, social media, and computer vision are moving towards analyzing the data using Graph Convolutions. This seminar provides a space for discussion of the recent scientific publications on GCN with a focus on their medical applications and others.


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