Goal: Provide an overview of the most prominent papers and topics in graph learning, with an emphasis on deep learning methods.
Weekly Tasks: Read one paper, write a 1-2 page summary explaining the key ideas, limitations, and suggestions for overcoming those limitations.
Lecture Weeks: Every 2-3 students will be assigned a topic. Their task is to prepare and deliver a 2-hour presentation synthesizing 3-5 papers on that topic into a coherent narrative. The presentation should include all relevant background information to understand the context, as well as a 5-10 minute live demonstration of a related technique using code.
Grading: Presentations: 70% Weekly Paper Summaries/Critiques: 30%
relevant books:
- מורה: חגי מרון