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There has been considerable recent activity applying deep convolutional neural nets (CNNs) to data from particle physics experiments.
LeCun Y, Bottou L, Bengio Y and Haffner P 1998 Proceedings of the IEEE
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Sjöstrand T, Mrenna S and Skands P 2008 Computer Physics Communications
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Nair V and Hinton G E 2010 Proceedings of ICML-10
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Cacciari M, Salam G P and Soyez G 2012 The European Physical Journal C
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de Favereau J, Delaere C et al
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Adam-Bourdarios C, Cowan G, Germain C, Guyon I, Kegl B and Rousseau D 2014 URL http://higgsml.lal.in2p3.fr/documentation
2014
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ATLAS Collaboration 2016 Search for massive supersymmetric particles in multi-jet final states produced in pp collisions at s = \sqrt{s}\penalty\ = 13 TeV using the ATLAS detector at the LHC Tech. Rep. ATLAS-CONF-2016-057 CERN Geneva URL http://cds.cern.ch/record/2206149
2016
Cited alongside, same era.
de Oliveira L, Kagan M, Mackey L, Nachman B and Schwartzman A 2016 JHEP
2016
Cited alongside, same era.
Komiske P T, Metodiev E M and Schwartz M D 2017 JHEP
2017
Cited alongside, same era.
2017 TensorFlow version 1.2.0 https://github.com/tensorflow/tensorflow/releases/tag/v1.2.0
2017
Cited alongside, same era.
2017 TensorFlow Optimizations on Modern Intel Architecture https://software.intel.com/en-us/articles/tensorflow-optimizations-on-modern-intel-architecture
2017
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2017 Introducing DNN primitives in Intel Math Kernel Library https://software.intel.com/en-us/articles/introducing-dnn-primitives-in-intelr-mkl
2017
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2017 Intel distribution of Caffe* https://github.com/intel/caffe
2017
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2017 Intel Machine Learning Scaling Library for Linux OS https://github.com/01org/MLSL
2017
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2017
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