5 papers
Efficient AI-Inspired Reduction of Feynman Integrals via Tube Seeding
Justin Berman, Francois Charton, Andres Luna +2
In this paper, we use machine learning to discover a new seeding strategy for integration-by-parts reduction of Feynman integrals, which is a frequent bottleneck in state-of-the-ar…
Extrapolating Jet Radiation with Autoregressive Transformers
Anja Butter, François Charton, Javier Mariño Villadamigo +3
Generative networks are an exciting tool for fast LHC event fixed number of particles. Autoregressive transformers allow us to generate events containing variable numbers of partic…
Recurrent Features of Amplitudes in Planar Super Yang-Mills Theory
Tianji Cai, François Charton, Kyle Cranmer +3
The planar three-gluon form factor for the chiral stress tensor operator in planar maximally supersymmetric Yang-Mills theory is an analog of the Higgs-to-three-gluon scattering am…
Int2Int: a framework for mathematics with transformers
François Charton
This paper documents Int2Int, an open source code base for using transformers on problems of mathematical research, with a focus on number theory and other problems involving integ…
Is Tokenization Needed for Masked Particle Modelling?
Matthew Leigh, Samuel Klein, François Charton +5
In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets releva…