3 papers
stat.ML2026
Learning the Graphical Nature of Symmetries
Rashid Barket, Enrico Grimaldi, Yacoub Hendi +3
Finite groups are rigid algebraic objects, whose Cayley graphs expose a rich network geometry through which group-theoretic structure can be measured, compared, and learned. In thi…
cs.LG2026
The Geometry of Polynomial Group Convolutional Neural Networks
Yacoub Hendi, Daniel Persson, Magdalena Larfors
We study polynomial group convolutional neural networks (PGCNNs) for an arbitrary finite group . In particular, we introduce a new mathematical framework for PGCNNs using the la…
hep-th2024
Learning Group Invariant Calabi-Yau Metrics by Fundamental Domain Projections
Yacoub Hendi, Magdalena Larfors, Moritz Walden
We present new invariant machine learning models that approximate the Ricci-flat metric on Calabi-Yau (CY) manifolds with discrete symmetries. We accomplish this by combining the $…