Jet diffusion versus JetGPT – Modern networks for the LHC

We introduce two diffusion models and an autoregressive transformer for LHC physics simulations. Bayesian versions allow us to control the networks and capture training uncertainties. After illustrating their different density estimation methods for simple toy models, we discuss their advantages for...

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Bibliographic Details
Main Author: Anja Butter, Nathan Huetsch, Sofia Palacios Schweitzer, Tilman Plehn, Peter Sorrenson, Jonas Spinner
Format: Article
Language:English
Published: SciPost 2025-03-01
Series:SciPost Physics Core
Online Access:https://scipost.org/SciPostPhysCore.8.1.026
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