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Deep learning is finding its way into high energy physics by replacing traditional Monte Carlo simulations.
GEANT4–a simulation toolkit
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Ieee standard for floating-point arithmetic
IEEE (2008) · 2008
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Electromagnetic calorimetry
Brown, R. and Cockerill, D. (2012) · 2012
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Generative adversarial networks
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014) · 2014
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Deep residual learning for image recognition
He, K. et al. (2015) · 2015
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Rethinking the inception architecture for computer vision
Szegedy, C. et al. (2015) · 2015
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High-Luminosity Large Hadron Collider (HL-LHC): Technical Design Report V. 0.1
Apollinari, G. et al. (2017) · 2017
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Wasserstein gan
Arjovsky, M., Chintala, S., and Bottou, L. (2017) · 2017
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Learning particle physics by example: Location-aware generative adversarial networks for physics synthesis
de Oliveira, L. and Paganini, Michela, B. (2017) · 2017
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Mixed precision training
Micikevicius, P. et al. (2017) · 2017
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Pros and cons of gan evaluation measures
Borji, A. (2018) · 2018
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Three dimensional energy parametrized generative adversarial networks for electromagnetic shower simulation
Khattak, G., Vallecorsa, S., and Carminati, F. (2018) · 2018
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Deep generative models for fast shower simulation in atlas
Salamani, D. et al. (2018) · 2018
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A roadmap for hep software and computing r&d for the 2020s
Albrecht et al. (2019) · 2019
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3d convolutional gan for fast simulation
Vallecorsa, S., Carminati, F., and Khattak, G. (2019) · 2019
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Inference at reduced precision on gpus
Wu, H. (2019) · 2019
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TensorFlow Lite
(2020) · 2020
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18 Impressive Applications of Generative Adversarial Networks (GANs)
Brownlee, J. (2020) · 2020
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Efficient execution of quantized deep learning models: A compiler approach
Jain, A. et al. (2020) · 2020
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Mixed-precision deep learning based on computational memory
Nandakumar, S. R. et al. (2020) · 2020
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Intel® low precision optimization tool
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Precise simulation of electromagnetic calorimeter showers using a wasserstein generative adversarial network
Erdmann M., G. J. . Q. T. (2019) · 2019
Cited alongside, same era.
Deep generative models for fast shower simulation in ATLAS
Ghosh, A. (2019) · 2019
Cited alongside, same era.
oneapi deep neural network library (onednn)
Intel
Cited in the paper.
Evaluating mixed-precision arithmetic for 3d generative adversarial networks to simulate high energy physics detectors
Osorio, J
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Tian, F. et al. (2020) · 2020
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Integer quantization for deep learning inference: Principles and empirical evaluation
Wu, H. et al. (2020) · 2020
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