most citedHomogeneous vector bundles and -equivariant convolutional neural networks

14 citations · 25 across the 3 of their papers we have counts for

collaborators

3 papers

hep-lat2023★ 6 cited

Geometrical aspects of lattice gauge equivariant convolutional neural networks

Jimmy Aronsson, David I. Müller, Daniel Schuh

Lattice gauge equivariant convolutional neural networks (L-CNNs) are a framework for convolutional neural networks that can be applied to non-Abelian lattice gauge theories without…

cs.LG2021★ 5 cited

Geometric Deep Learning and Equivariant Neural Networks

Jan E. Gerken, Jimmy Aronsson, Oscar Carlsson +4

We survey the mathematical foundations of geometric deep learning, focusing on group equivariant and gauge equivariant neural networks. We develop gauge equivariant convolutional n…

cs.LG2021★ 14 cited

Homogeneous vector bundles and -equivariant convolutional neural networks

Jimmy Aronsson

-equivariant convolutional neural networks (GCNNs) is a geometric deep learning model for data defined on a homogeneous -space . GCNNs are designed to respect th…