17 citations · 40 across the 6 of their papers we have counts for
3 papers · 1 filter
A Lorentz-Equivariant Transformer for All of the LHC
Johann Brehmer, Víctor Bresó, Pim de Haan +4
We show that the Lorentz-Equivariant Geometric Algebra Transformer (L-GATr) yields state-of-the-art performance for a wide range of machine learning tasks at the Large Hadron Colli…
Does equivariance matter at scale?
Johann Brehmer, Sönke Behrends, Pim de Haan +1
Given large datasets and sufficient compute, is it beneficial to design neural architectures for the structure and symmetries of each problem? Or is it more efficient to learn them…
Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics
Jonas Spinner, Victor Bresó, Pim de Haan +3
Extracting scientific understanding from particle-physics experiments requires solving diverse learning problems with high precision and good data efficiency. We propose the Lorent…