Speaker
Sofia Palacios Schweitzer
(ITP, University Heidelberg)
Description
Given the recent success of diffusion models in image generation, we study their applicability to generating LHC phase space distributions. We find that they achieve percent level precision comparable to INNs. To further enhance the interpretability of our results we quantify our training uncertainty by developing Bayesian versions. In this talk, diffusion models are introduced and discussed followed by a presentation of our findings.
Primary authors
Anja Butter
(Centre National de la Recherche Scientifique (FR))
Jonas Simon Spinner
Nathan Huetsch
(Institut für Theoretische Physik, Universität Heidelberg)
Peter Rangi Sorrenson
(Universität Heidelberg)
Sofia Palacios Schweitzer
(ITP, University Heidelberg)
Tilman Plehn
