Lab Course: Graph Learning
Summer term 2022
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.
Prerequisites
This practical course is only addressed to master students in the MSc Computer Science and MSc Data Science programmes.
No previous knowledge is required. Knowledge from the courses Algorithmic Foundations of Data Science, 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
Assistants:
Jan Tönshoff