6 citations · 11 across the 2 of their papers we have counts for
3 papers
Enhancing generalization in high energy physics using white-box adversarial attacks
Franck Rothen, Samuel Klein, Matthew Leigh +1
Machine learning is becoming increasingly popular in the context of particle physics. Supervised learning, which uses labeled Monte Carlo (MC) simulations, remains one of the most…
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…
Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation
Samuel Klein, John Andrew Raine, Tobias Golling
Normalizing flows are constructed from a base distribution with a known density and a diffeomorphism with a tractable Jacobian. The base density of a normalizing flow can be parame…