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@ARTICLE{Collaboration:795340,
author = {CMS Collaboration and others},
collaboration = {{CMS Collaboration}},
title = {{I}dentification of heavy, energetic, hadronically decaying
particles using machine-learning techniques},
journal = {Journal of Instrumentation},
volume = {15},
number = {6},
issn = {1748-0221},
address = {London},
publisher = {Inst. of Physics},
reportid = {RWTH-2020-08265},
pages = {P06005},
year = {2020},
keywords = {13000 GeV-cms (INSPIRE) / CERN LHC Coll (INSPIRE) / CMS
(INSPIRE) / Higgs particle: hadronic decay (INSPIRE) / W:
hadronic decay (INSPIRE) / Z0: hadronic decay (INSPIRE) /
background (INSPIRE) / boosted particle (INSPIRE) / data
analysis method (INSPIRE) / experimental results (INSPIRE) /
neural network (INSPIRE) / numerical calculations: Monte
Carlo (INSPIRE) / p p: colliding beams (INSPIRE) / p p:
scattering (INSPIRE) / particle identification: efficiency
(INSPIRE) / particle identification: performance (INSPIRE) /
statistical analysis (INSPIRE) / top: hadronic decay
(INSPIRE)},
cin = {131410 / 133110 / 133510 / 131520 / 130000 / 131910 /
133320 / 133920},
ddc = {610},
cid = {$I:(DE-82)131410_20140620$ / $I:(DE-82)133110_20140620$ /
$I:(DE-82)133510_20140620$ / $I:(DE-82)131520_20140620$ /
$I:(DE-82)130000_20140620$ / $I:(DE-82)131910_20160614$ /
$I:(DE-82)133320_20140620$ / $I:(DE-82)133920_20180228$},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000545350900005},
doi = {10.1088/1748-0221/15/06/P06005},
url = {https://publications.rwth-aachen.de/record/795340},
}
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