Speaker
Sebastian Pitz
(ITP, Heidelberg University)
Description
We construct Lorentz-equivariant transformer and graph networks using the concept of local canonicalization. While many Lorentz-equivariant architectures use specialized layers, this approach allows to take any existing non-equivariant architecture and make it Lorentz-equivariant using transformations with equivariantly predicted local frames. In addition, data augmentation emerges as a special case of this approach, allowing us to directly compare data augmentation with equivariant models. We use the task-specific non-equivariant architectures in amplitude regression and jet tagging to benchmark local canonicalization.
References
https://arxiv.org/abs/2411.00446
Authors
Jonas Spinner
(ITP, Heidelberg University)
Sebastian Pitz
(ITP, Heidelberg University)
Luigi Favaro
(Universite Catholique de Louvain (UCL) (BE))
Tilman Plehn
(ITP, Heidelberg University)
Mr
Gerrit Gerhartz
(ITP, Heidelberg University)
Mr
Peter Lippmann
(IWR, Heidelberg University)
