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1 |
Tree-based algorithms for weakly supervised anomaly detection
Finke, Thorben. - Aachen : Universitätsbibliothek der RWTH Aachen, 2024
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2 |
Searching for Dark Matter produced in association with top quarks with the CMS experiment at the LHC
Stafford, Dominic William. - Hamburg : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2023
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3 |
Shared Data and Algorithms for Deep Learning in Fundamental Physics
Benato, Lisa. - Aachen : Universitätsbibliothek der RWTH Aachen, 2022
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4 |
Getting high: high fidelity simulation of high granularity calorimeters with high speed
Buhmann, Erik. - Hamburg : Deutsches Elektronen-Synchrotron DESY, May 2020
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5 |
The Machine Learning landscape of top taggers
Kasieczka, Gregor. - Aachen : Universitätsbibliothek der RWTH Aachen, 2019
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6 |
Search for resonances decaying into top quark pairs using fully hadronic decays in pp collisions with ATLAS at √s= 7 TeV
Kasieczka, Gregor, 2013
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7 |
Search for Resonances Decaying into Top Quark Pairs Using Fully Hadronic Decays in pp Collisions with ATLAS at sqrt(s) = 7 TeV
Kasieczka, Gregor. - Heidelberg : Universitätsbibliothek Heidelberg, 2013
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8 |
Classifier surrogates: sharing AI-based searches with the world
Enthalten in The European physical journal / C / Particles and fields Bd. 84, 27.9.2024, Nr. 9, date:9.2024: 1-10
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9 |
Deep-learning top taggers or the end of QCD?
Enthalten in Journal of high energy physics Bd. 2017, 2.5.2017, Nr. 5, date:5.2017: 1-22
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10 |
Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed
Enthalten in Computing and software for big science Bd. 5, 26.5.2021, Nr. 1, date:12.2021: 1-17
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