Weakly supervised classification in high energy physics

Dery, Lucio Mwinmaarong; Nachman, Benjamin; Rubbo, Francesco; Schwartzman, Ariel

doi:10.1007/JHEP05(2017)145

Title: Weakly supervised classification in high energy physics

Journal Article · Mon May 01 00:00:00 EDT 2017 · Journal of High Energy Physics (Online)

DOI:https://doi.org/10.1007/JHEP05(2017)145· OSTI ID:1369428

Dery, Lucio Mwinmaarong ^[1]; Nachman, Benjamin ^[2];

^[3]; Schwartzman, Ariel ^[3]

Stanford Univ., CA (United States). Dept. of Physics
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physics Division
SLAC National Accelerator Lab., Menlo Park, CA (United States)

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Research Organization:: SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC02-76SF00515; AC02-05CH11231

OSTI ID:: 1369428

Alternate ID(s):: OSTI ID: 1379863

Journal Information:: Journal of High Energy Physics (Online), Vol. 2017, Issue 5; ISSN 1029-8479

Publisher:: Springer BerlinCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 68 works

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References (39)

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Sedimentation mapping in shallow shoreline of arid environments using active remote sensing data Elhag, Mohamed; Bahrawi, Jarbou A. Natural Hazards, Vol. 99, Issue 2 https://doi.org/10.1007/s11069-019-03780-4	journal	September 2019
A framework for evaluation in learning from label proportions Hernández-González, Jerónimo Progress in Artificial Intelligence, Vol. 8, Issue 3 https://doi.org/10.1007/s13748-019-00187-x	journal	May 2019
Identifying the Relevant Dependencies of the Neural Network Response on Characteristics of the Input Space Wunsch, Stefan; Friese, Raphael; Wolf, Roger Computing and Software for Big Science, Vol. 2, Issue 1 https://doi.org/10.1007/s41781-018-0012-1	journal	September 2018
On asymptotic charges in 3D gravity Bergshoeff, Eric A.; Merbis, Wout; Townsend, Paul K. Classical and Quantum Gravity, Vol. 37, Issue 3 https://doi.org/10.1088/1361-6382/ab5ea5	journal	January 2020
Guiding new physics searches with unsupervised learning De Simone, Andrea; Jacques, Thomas The European Physical Journal C, Vol. 79, Issue 4 https://doi.org/10.1140/epjc/s10052-019-6787-3	journal	March 2019
On asymptotic charges in 3D gravity Bergshoeff, Ea; Merbis, W.; Townsend, Paul Apollo - University of Cambridge Repository https://doi.org/10.17863/cam.49860	text	January 2020
Automating the construction of jet observables with machine learning Datta, Kaustuv; Larkoski, Andrew; Nachman, Benjamin ETH Zurich https://doi.org/10.3929/ethz-b-000380014	text	January 2019
The Machine Learning landscape of top taggers Kasieczka, Gregor; Plehn, Tilman; Butter, Anja RWTH Aachen University https://doi.org/10.18154/rwth-2019-07568	text	January 2019
Systematics of quark/gluon tagging Gras, Philippe; Höche, Stefan; Kar, Deepak arXiv https://doi.org/10.48550/arxiv.1704.03878	text	January 2017
(Machine) Learning to Do More with Less Cohen, Timothy; Freytsis, Marat; Ostdiek, Bryan arXiv https://doi.org/10.48550/arxiv.1706.09451	text	January 2017
Energy flow polynomials: A complete linear basis for jet substructure Komiske, Patrick T.; Metodiev, Eric M.; Thaler, Jesse arXiv https://doi.org/10.48550/arxiv.1712.07124	text	January 2017
Learning to Classify from Impure Samples with High-Dimensional Data Komiske, Patrick T.; Metodiev, Eric M.; Nachman, Benjamin arXiv https://doi.org/10.48550/arxiv.1801.10158	text	January 2018
Identifying the relevant dependencies of the neural network response on characteristics of the input space Wunsch, Stefan; Friese, Raphael; Wolf, Roger arXiv https://doi.org/10.48550/arxiv.1803.08782	text	January 2018
Energy Flow Networks: Deep Sets for Particle Jets Komiske, Patrick T.; Metodiev, Eric M.; Thaler, Jesse arXiv https://doi.org/10.48550/arxiv.1810.05165	text	January 2018
Investigating the Topology Dependence of Quark and Gluon Jets Bright-Thonney, Samuel; Nachman, Benjamin arXiv https://doi.org/10.48550/arxiv.1810.05653	text	January 2018
Automating the Construction of Jet Observables with Machine Learning Datta, Kaustuv; Larkoski, Andrew; Nachman, Benjamin arXiv https://doi.org/10.48550/arxiv.1902.07180	text	January 2019
Interpretable Deep Learning for Two-Prong Jet Classification with Jet Spectra Chakraborty, Amit; Lim, Sung Hak; Nojiri, Mihoko M. arXiv https://doi.org/10.48550/arxiv.1904.02092	text	January 2019
A Theory of Quark vs. Gluon Discrimination Larkoski, Andrew J.; Metodiev, Eric M. arXiv https://doi.org/10.48550/arxiv.1906.01639	text	January 2019
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