Rita Fioresi
Geometric Deep Learning meets Quantum Groups: a quantum differential calculus approach to differential geometry on graphs for machine learning
The recent advancements in machine learning have prompted interest in discrete differential geometry. In this talk we present some state of the art techniques as sheaf neural networks in geometric deep learning and their interpretation via quantum differential calculus and quantum principal bundles, together with the quantum notions of connection and curvature.
