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Over the past five years, modern machine learning has been quietly revolutionizing particle physics.
“AI Feynman: a physics-inspired method for symbolic regression”, 2019
Silviu-Marian Udrescu and Max Tegmark · 1905
Earlier work this paper cites.
“ABCDisCo: automating the ABCD Method with machine learning”, 2020
Gregor Kasieczka, Benjamin Nachman, Matthew. Schwartz and David Shih · 2007
Earlier work this paper cites.
“The catchment area of jets”
Matteo Cacciari, Gavin. Salam and Gregory Soyez · 2008
Earlier work this paper cites.
“Top Tagging: a method for identifying boosted hadronically decaying top quarks”
David. Kaplan, Keith Rehermann, Matthew. Schwartz and Brock Tweedie · 2008
Earlier work this paper cites.
“Pure samples of quark and gluon jets at the LHC”
Jason Gallicchio and Matthew. Schwartz · 2011
Earlier work this paper cites.
“Pileup removal algorithms”
CMS · 2014
Earlier work this paper cites.
“Jet-Images: computer vision inspired techniques for jet tagging”
Josh Cogan, Michael Kagan, Emanuel Strauss and Ariel Schwarztman · 2015
Earlier work this paper cites.
“A convolutional neural network neutrino event classifier”
A. Aurisano et al · 2016
Earlier work this paper cites.
“Learning to pivot with adversarial networks”, 2016
Gilles Louppe, Michael Kagan and Kyle Cranmer · 2016
Cited alongside, same era.
“Deep-learning top taggers or the end of QCD?”
Gregor Kasieczka, Tilman Plehn, Michael Russell and Torben Schell · 2017
Cited alongside, same era.
“Pileup Mitigation with Machine Learning (PUMML)”
Patrick. Komiske, Eric. Metodiev, Benjamin Nachman and Matthew. Schwartz · 2017
Cited alongside, same era.
“Classification without labels: learning from mixed samples in high energy physics”
Eric. Metodiev, Benjamin Nachman and Jesse Thaler · 2017
Cited alongside, same era.
“Learning to classify from impure samples with high-dimensional data”
Patrick. Komiske, Eric. Metodiev, Benjamin Nachman and Matthew. Schwartz · 2018
Cited alongside, same era.
“Expected performance of the 2019 ATLAS b b -taggers”, 2019
ATLAS · 2019
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“Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC”
ATLAS · 2019
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“Etalumis: bringing probabilistic programming to scientific simulators at scale”, 2019
Atılımüneş Baydin · 2019
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“The machine learning landscape of top taggers”
Anja Butter · 2019
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“Data science applications to string theory”
Fabian Ruehle · 2019
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“Dynamic graph CNN for learning on point clouds”
Yue Wang et al · 2019
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Michela Paganini, Luke de Oliveira and Benjamin Nachman · 2018
Cited alongside, same era.
“Machine learning action parameters in lattice quantum chromodynamics”
Phiala. Shanahan, Daniel Trewartha and William Detmold · 2018
Cited alongside, same era.
“Binary JUNIPR: an interpretable probabilistic model for discrimination”
Anders Andreassen, Ilya Feige, Christopher Frye and Matthew. Schwartz · 2019
Cited alongside, same era.
“OmniFold: A method to simultaneously unfold all observables”
Anders Andreassen et al · 2020
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“Jet tagging via particle clouds”
Huilin Qu and Loukas Gouskos · 2020
Later among the works it cites.