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1.
End-to-End Jet Classification of Boosted Top Quarks with CMS Open Data / Andrews, Michael (Carnegie Mellon U.) ; Burkle, Bjorn (Brown U.) ; Chen, Yi-fan (Digital Pathways, Mtn. View) ; DiCroce, Davide (Alabama U.) ; Gleyzer, Sergei (Alabama U.) ; Heintz, Ulrich (Brown U.) ; Narain, Meenakshi (Brown U.) ; Paulini, Manfred (Carnegie Mellon U.) ; Pervan, Nikolas (Brown U.) ; Shafi, Yusef (Google Inc. ; Digital Pathways, Mtn. View) et al.
We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation of the high-energy collision event. [...]
arXiv:2104.14659.- 2021 - 9 p. - Published in : EPJ Web Conf.: 251 (2021) , pp. 04030
- Published in : Phys. Rev. D Fulltext: 2104.14659 - PDF; document - PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.04030
Detailed record
2.
Machine Learning in High Energy Physics Community White Paper / Albertsson, Kim (Lulea U.) ; Altoe, Piero (NVIDIA, Santa Clara) ; Anderson, Dustin (Caltech) ; Anderson, John ; Andrews, Michael (Carnegie Mellon U.) ; Araque Espinosa, Juan Pedro (LIP, Lisbon) ; Aurisano, Adam (Cincinnati U.) ; Basara, Laurent (INFN, Padua ; Padua U.) ; Bevan, Adrian (University Coll. London) ; Bhimji, Wahid (LBL, Berkeley) et al.
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas for machine learning in particle physics. [...]
arXiv:1807.02876; FERMILAB-PUB-18-318-CD-DI-PPD.- 2018-10-18 - 27 p. - Published in : J. Phys.: Conf. Ser. 1085 (2018) 022008 Fulltext: Albertsson_2018_J._Phys.__Conf._Ser._1085_022008 - PDF; 1807.02876 - PDF; fermilab-pub-18-318-cd-di-ppd - PDF; fulltext1681439 - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server (fulltext available)
In : 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Seattle, WA, USA, 21 - 25 Aug 2017, pp.022008
Detailed record

See also: similar author names
93 Yang, K
1 Yang, K ;
37 Yang, K C
5 Yang, K H
1 Yang, K M
4 Yang, K Q
52 Yang, K S
1 Yang, K W
2 Yang, K Y
15 Yang, K.
5 Yang, K.Z.
6 Yang, Kai
2 Yang, Kaike
1 Yang, Kan
106 Yang, Kang
2 Yang, Karan
21 Yang, Ke
1 Yang, Kesheng
4 Yang, Kevin
8 Yang, Ki Youl
3 Yang, Kia-Jung
4 Yang, Kichoon
1 Yang, Kun-Lin
1 Yang, Kung-Wei
2 Yang, KwangSoo
24 Yang, Kwei-Chou
2 Yang, Kyeongcheol
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