Deep learning at 15PF
Author:
Affiliation:
1. NERSC
2. Stanford University
3. Intel Corporation
4. Intel Corporation, Nizhny Novgorod, Russian Federation
5. Intel Corporation, Bangalore, Karnataka, India
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3126908.3126916
Reference52 articles.
1. Track finding with neural networks
2. Neural networks and cellular automata in experimental high energy physics
3. Jet-images — deep learning edition
4. Deep learning in color: towards automated quark/gluon jet discrimination
5. The ATLAS collaboration "Search for massive supersymmetric particles in multi-jet final states produced in pp collisions at {EQUATION} = 13 TeV using the ATLAS detector at the LHC " ATLAS-CONF-2016-057 2016. The ATLAS collaboration "Search for massive supersymmetric particles in multi-jet final states produced in pp collisions at {EQUATION} = 13 TeV using the ATLAS detector at the LHC " ATLAS-CONF-2016-057 2016.
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