Touranakou, Mary https://orcid.org/0000-0002-3682-3258
Chernyavskaya, Nadezda https://orcid.org/0000-0002-2264-2229
Duarte, Javier https://orcid.org/0000-0002-5076-7096
Gunopulos, Dimitrios https://orcid.org/0000-0001-6339-1879
Kansal, Raghav https://orcid.org/0000-0003-2445-1060
Orzari, Breno https://orcid.org/0000-0003-4232-4743
Pierini, Maurizio https://orcid.org/0000-0003-1939-4268
Tomei, Thiago https://orcid.org/0000-0002-1809-5226
Vlimant, Jean-Roch https://orcid.org/0000-0002-9705-101X
Funding for this research was provided by:
IRIS
H2020 European Research Council (772369)
LHC Physics Center
National Science Foundation (OAC-1836650)
U.S. Department of Energy
Fermi Research Alliance, LLC (DE-AC02-07CH11359)
TAILOR (952215)
High Energy Physics (DE-AC02-07CH11359)
São Paulo Research Foundation (2020/06600-3)
SãoPaulo Research Foundation (2018/25225-9)
University of California
NSF (ACI-1540112)
California Institute for Telecommunications
University of California San Diego
CENIC
Information Technology/Qualcomm
Article Title: Particle-based fast jet simulation at the LHC with variational autoencoders
Journal Title: Machine Learning: Science and Technology
Article Type: paper
Copyright Information: © 2022 The Author(s). Published by IOP Publishing Ltd
Publication dates
Date Received: 2022-04-01
Date Accepted: 2022-06-27
Online publication date: 2022-07-13