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Using generative adversarial networks (GANs), we investigate the possibility of creating large amounts of analysis-specific simulated LHC events at limited computing cost.
Calculation of the neutron-induced background in the Gargamelle neutral current search
W F Fry and Dieter Haidt · 1975
Earlier work this paper cites.
GEANT4: A Simulation toolkit
S. Agostinelli et al · 2003
Earlier work this paper cites.
CMS Monte Carlo production in the WLCG computing grid
Jose M. Hernandez et al · 2008
Earlier work this paper cites.
The CMS Experiment at the CERN LHC
S. Chatrchyan et al · 2008
Earlier work this paper cites.
The anti- k t k_{t} jet clustering algorithm
Matteo Cacciari, Gavin P. Salam, and Gregory Soyez · 2008
Earlier work this paper cites.
Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC
Georges Aad et al · 2012
Earlier work this paper cites.
Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC
Serguei Chatrchyan et al · 2012
Earlier work this paper cites.
Rethinking particle transport in the many-core era towards geant 5
Carminati F Apostolakis J, Brun R and Gheata A · 2012
Earlier work this paper cites.
ADADELTA: an adaptive learning rate method
Matthew D. Zeiler · 2012
Earlier work this paper cites.
Generative Adversarial Networks
I. J. Goodfellow et al · 2014
Earlier work this paper cites.
DELPHES 3, A modular framework for fast simulation of a generic collider experiment
J. de Favereau et al · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
High Luminosity Large Hadron Collider HL-LHC
G. Apollinari, O. Brüning, T. Nakamoto, and Lucio Rossi · 2015
Earlier work this paper cites.
Technical Proposal for the Phase-II Upgrade of the CMS Detector
V. Khachatryan et al · 2015
Cited alongside, same era.
The geantv project: preparing the future of simulation
G Amadio et al · 2015
Cited alongside, same era.
An Introduction to PYTHIA 8.2
Torbjörn Sjöstrand et al · 2015
Cited alongside, same era.
keras, 2015
François Chollet · 2015
Cited alongside, same era.
TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi et al · 2015
Cited alongside, same era.
Learning to Pivot with Adversarial Networks
Gilles Louppe, Michael Kagan, and Kyle Cranmer · 2016
Cited alongside, same era.
Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis
Measurement of the cross section for top quark pair production in association with a W or Z boson in proton-proton collisions at s = \sqrt{s}= 13 TeV
Albert M Sirunyan et al · 2018
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Measurement of the top quark polarization and t t ¯ \mathrm{t\bar{t}} spin correlations in dilepton final states at s = 13 TeV \sqrt{s}=13\penalty\ \mathrm{TeV}
CMS Collaboration · 2018
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Fast and Accurate Simulation of Particle Detectors Using Generative Adversarial Networks
Pasquale Musella and Francesco Pandolfi · 2018
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Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multilayer Calorimeters
Michela Paganini, Luke de Oliveira, and Benjamin Nachman · 2018
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CaloGAN : Simulating 3D high energy particle showers in multilayer electromagnetic calorimeters with generative adversarial networks
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Luke de Oliveira, Michela Paganini, and Benjamin Nachman · 2017
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Particle-flow reconstruction and global event description with the cms detector
A.M. Sirunyan and etal · 2017
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Calorimetry with Deep Learning: Particle Classification, Energy Regression, and Simulation for High-Energy Physics
B. Hooberman et al · 2017
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Efficient Monte Carlo Integration Using Boosted Decision Trees and Generative Deep Neural Networks
Joshua Bendavid · 2017
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Decorrelated Jet Substructure Tagging using Adversarial Neural Networks
Chase Shimmin et al · 2017
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An MPI-based Python framework for distributed training with Keras
Dustin Anderson, Maria Spiropulu, and Jean-Roch Vlimant · 2017
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Michela Paganini, Luke de Oliveira, and Benjamin Nachman · 2018
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Precise simulation of electromagnetic calorimeter showers using a Wasserstein Generative Adversarial Network
Martin Erdmann, Jonas Glombitza, and Thorben Quast · 2018
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A Deep Learning-based Reconstruction of Cosmic Ray-induced Air Showers
M. Erdmann, J. Glombitza, and D. Walz · 2018
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HEP Software Foundation Community White Paper Working Group - Detector Simulation
J Apostolakis et al · 2018
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Variational Autoencoders for New Physics Mining at the Large Hadron Collider
Olmo Cerri et al · 2018
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QCD or What?
Theo Heimel et al · 2018
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Unfolding with Generative Adversarial Networks
Kaustuv Datta, Deepak Kar, and Debarati Roy · 2018
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Event Generation and Statistical Sampling with Deep Generative Models
Sydney Otten et al · 2019
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