CMSA New Technologies in Mathematics Seminar: Neural diffusion PDEs, differential geometry, and graph neural networks
CMSA EVENTS
Speaker:
Michael Bronstein - University of Oxford / Twitter
In this talk, I will make connections between Graph Neural Networks (GNNs) and non-Euclidean diffusion equations. I will show that drawing on methods from the domain of differential geometry, it is possible to provide a principled view on such GNN architectural choices as positional encoding and graph rewiring as well as explain and remedy the phenomena of oversquashing and bottlenecks.
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