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Calorimeter simulation is the most computationally expensive part of Monte Carlo generation of samples necessary for analysis of experimental data at the Large Hadron Collider (LHC).
Calculation of the capture of negative pions in light elements and comparison with experiments pertaining to cancer radiotherapy
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The Parameterized simulation of electromagnetic showers in homogeneous and sampling calorimeters
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Final state interactions in the (nuclear) FRITIOF string interaction scenario
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Modified FRITIOF code: Negative charged particle production in high energy nucleus nucleus interactions
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GEANT4–a simulation toolkit
S. Agostinelli et al · 2003
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Geant4 standard electromagnetic package for HEP applications
H. Burkhardt et al · 2004
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The atlas simulation infrastructure
G. Aad et al · 2010
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The simulation principle and performance of the ATLAS fast calorimeter simulation FastCaloSim
M. Beckingham et al · 2010
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The fast simulation of the CMS experiment
R. Rahmat et al · 2012
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Common Accounting System for Monitoring the ATLAS Distributed Computing Resources
E. Karavakis et al · 2014
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
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Stochastic backpropagation and approximate inference in deep generative models
D. J. Rezende et al · 2014
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LHCb Computing Resource usage in 2014 (II)
C. Bozzi · 2015
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Upgrade of the ATLAS Liquid Argon Calorimeters for the High-Luminosity LHC
T. G. McCarthy · 2016
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Electromagnetic calorimeter shower images, 2017
B. Nachman et al · 2017
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Calogan: Simulating 3d high energy particle showers in multilayer electromagnetic calorimeters with generative adversarial networks
M. Paganini et al · 2018
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Technical report, CERN, Geneva, Jul 2018
Deep generative models for fast shower simulation in ATLAS · 2018
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Dvae++: Discrete variational autoencoders with overlapping transformations
A. Vahdat et al · 2018
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Gumbolt: Extending gumbel trick to boltzmann priors
A. H. Khoshaman and M. H. Amin · 2018
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Quantum variational autoencoder
A. Khoshaman et al · 2018
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The new ATLAS Fast Calorimeter Simulation
F. Dias · 2016
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Discrete variational autoencoders
J. T. Rolfe · 2016
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Categorical reparameterization with gumbel-softmax
E. Jang et al · 2016
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The concrete distribution: A continuous relaxation of discrete random variables
C. J. Maddison et al · 2016
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Learning particle physics by example: location-aware generative adversarial networks for physics synthesis
L. de Oliveira et al · 2017
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Quantum boltzmann machine
M. H. Amin et al · 2018
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ATLAS HL-LHC Computing Conceptual Design Report
P. Calafiura et al · 2020
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A path towards quantum advantage in training deep generative models with quantum annealers
W. Vinci et al · 2020
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Experiment tracking with weights and biases, 2020
L. Biewald · 2020
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Atlfast3: the next generation of fast simulation in atlas, 2021
ATLAS Collaboration · 2021
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