GLOW is a new reading group designed to foster discussions on the foundations and latest developments in Graph Machine Learning.
GLOW is a new reading group designed to foster discussions on the foundations and latest developments in Graph Machine Learning.
This time, we will have a three-part presentation and discussion. Based on the paper below, we will look into
Oversmoothing
Homophily vs. Heterophily
Oversquashing
Each part will be a short presentation followed by an open discussion.
Adrián Arnaiz-Rodríguez, Federico Errica
GLOW aims to create an inclusive and accessible environment that encourages interaction, especially for junior researchers and those outside major research labs.
Interactive Discussions: Unlike traditional reading groups dominated by long presentations, GLOW emphasizes small group discussions, breakout rooms, and active participation.
Diverse Formats: Our sessions will rotate through various formats, including 30-minute paper presentations followed by discussions, expert panel deep dives on specific topics, interview-style Q&A sessions with authors, and spotlight sessions for spontaneous brainstorming or early-stage ideas.
Thematic Focus: We plan to explore big themes over multiple sessions, such as invariance, expressivity, and the role of transformers in graph learning.