Lab Course: Graph Learning

 

Summer term 2020

Contact

Phone

work
+49 241 80 21706

Email

E-Mail
 
 

Content

In this practical course the participants will implement learning algorithms for graph data. This involves in particular topics such as graph kernels and graph neural networks which they will apply to different datasets.

Prerequisits

This practical course is only addressed to master students in the MSc Computer Science and MSc Data Science programmes.

No previous knowlege is required. Knowledge from the courses Algorithmic Foundations of Datascience, Algorithmic Learning Theory, Machine Learning are helpful, as well as knowledge of Python3 and Tensorflow.

 

Organization

The tasks will be worked upon by groups of two or three students.

Time and Place

Precise dates will be announced in RWTHonline before the semster starts.

The course will have a weekly meeting where results will be presented and possibly basics of graph learning will be presented.

Instructors

Martin Grohe

Assistants:
Martin Ritzert and Jan Tönshoff

 

External Links