The Data and Web Science seminar covers recent topics in data and web science. This term's topic is graph learning with a special (but not exclusive) focus on graph neural networks.
In this seminar, you will
Register via Portal 2 until Sep 6.
If you are accepted into the seminar, provide at least 4 topics of your preference (your own and/
Each student works on a topic within the area of the seminar along with an accompanying reference paper. Your presentation and report should explore the topic with an emphasis on the reference paper, but not just the reference paper.
We provide example topics and reference papers below. If you want, you may suggest a different reference paper (let us know after the topic assignment) or a different topic within the graph learning area (talk to us before the topic assignments). A good starting point is recent research papers in top data mining and machine learning conferences (e.g., try NeurIPS, ICLR, ICML, KDD).
Introductory lecture videos on graph learning (part of IE 674) will be made available to all participants. The following review articles may serve as further starting points:
All topics marked as „BSc topics“ can only be taken by BSc students. Unmarked topics are selected for MSc students, but can also be taken by BSc students with the appropriate background.
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