Graph Neural Networks (GNNs) are architectures for signal processing on graphs. GNNs explore the irregular structure of graph signals and exhibit superior performance in various wireless networks applications. This PhD course focuses on the fundamentals of and recent advances in graph learning as well as their application examples in wireless communications.
The focus will be on introduction to the concept of graph learning, representation of wireless networks as graph, application examples and provision of insights into latest development in graph learning to the students.
Organizer: Ramoni Adeogun
Lecturers: Ramoni Adeogun
ECTS: 2
Time: 22 - 23 May tentative
1 - 2 June
Place:
Zip code:
City:
Number of seats: 20
Deadline: 16 May
Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Ramoni Ojekunle Adeogun