Representative appearances

• The Geometric Deep Learning Blueprint — Michael Bronstein

  Professor and guest on the show, discussing the mathematical foundations of geometric deep learning, scale separation, and graph neural networks.

• Transformers Need Glasses! [Federico Barbero]

  Federico's supervisor, cited for work on graph neural networks and over-squashing.

• #85 Dr. Petar Veličković (Deepmind) - Categories, Graphs, Reasoning [NEURIPS22 UNPLUGGED]

  Researcher mentioned for concurrent work on curvature analysis in graph neural networks.

• #71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED]

  Cited for his foundational work on Geometric Deep Learning and graph diffusion.

• Why LeCun Thinks Deep Learning Isn't Enough — Yann LeCun