Lorentz Local Canonicalization (LLoCa) is a drop-in replacement that makes any network Lorentz-equivariant. Check out how we apply it to high-energy physics tasks in arxiv.org/abs/2505.20280. w/ Luigi Favaro, Peter Lippmann, Sebastian Pitz, Gerrit Gerhartz, Tilman Plehn, and Fred A. Hamprecht 1/6

Lorentz Local Canonicalization: How to Make Any Network Lorentz-Equivariant

Lorentz-equivariant neural networks are becoming the leading architectures for high-energy physics. Current implementations rely on specialized layers, limiting architectural choices. We introduce Lor...

arxiv.org

Can transformers learn the universal patterns of jet radiation and extrapolate beyond the training data? Find out in our preprint 'Extrapolating Jet Radiation with Autoregressive Transformers' arxiv.org/abs/2412.12074 w/ Javi Marino, Ayo Ore, Francois Charton, Anja Butter and Tilman Plehn 1/7

Extrapolating Jet Radiation with Autoregressive Transformers

Generative networks are an exciting tool for fast LHC event generation. Usually, they are used to generate configurations with a fixed number of particles. Autoregressive transformers allow us to gene...

arxiv.org

On Thursday from 11:00 to 14:00, I'll be cheering on @jonasspinner.bsky.social and Victor Bresó at poster 3911. They built L-GATr 🐊: a transformer that's equivariant to the Lorentz symmetry of special relativity. It performs remarkably well across different tasks in high-energy physics. 2/6

Thrilled to announce that L-GATr is going to NeurIPS 2024! Plus, there is a new preprint with extended experiments and a more detailed explanation. Code: github.com/heidelberg-h... Physics paper: arxiv.org/abs/2411.00446 CS paper: arxiv.org/abs/2405.14806 1/7

GitHub - heidelberg-hepml/lorentz-gatr: Repository for <Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics> (J. Spinner et al 2024)

Repository for <Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics> (J. Spinner et al 2024) - heidelberg-hepml/lorentz-gatr

github.com