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Dortmund 2021 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 71: Data analysis, Information technology III

Mittwoch, 17. März 2021, 16:00–18:15, Tu

16:00 T 71.1 Usage of neural networks in photon identification in ATLAS — •Florian Kirfel and Oleh Kivernyk
16:15 T 71.2 Studies of modern machine learning methods for tau lepton identification with the CMS detector — •Andrew Issac, Günter Quast, Roger Wolf, Stefan Wunsch, and Sebastian Brommer
16:30 T 71.3 Adversarial Neural Network-based shape calibrations of observables for jet-tagging at CMSMartin Erdmann, •Benjamin Fischer, Jan Middendorf, Dennis Noll, Yannik Alexander Rath, Marcel Rieger, Erwin Rudi, and David Josef Schmidt
16:45 T 71.4 AI-safety for jet flavour tagging at the CMS experimentXavier Coubez, Nikolas Frediani, Spandan Mondal, Andrzej Novak, Alexander Schmidt, and •Annika Stein
17:00 T 71.5 Charm jet identification and discriminator calibration with the CMS experiment — •Spandan Mondal, Xavier Coubez, Alena Dodonova, Luca Mastrolorenzo, Andrzej Novak, Andrey Pozdnyakov, and Alexander Schmidt
17:15 T 71.6 Performance Studies of the Integration of a Deep-Impact-Parameter-Setsbased Tagger for the ATLAS Experiment b-Tagging Algorithm — •Alexander Froch, Manuel Guth, and Andrea Knue
17:30 T 71.7 Training of an extended b-tagging algorithm with deep neural networks. — •Thea Engler, Manuel Guth, Gregor Herten, and Andrea Knue
17:45 T 71.8 Treating Uncertainties with Bayesian Neural Networks in a ttH Measurement — •Nikita Shadskiy and Ulrich Husemann
18:00 T 71.9 Improvement of the jet-parton assignment in ttH(bb) events using machine-learning techniques — •Daniel Bahner, Andrea Knue, and Gregor Herten
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DPG-Physik > DPG-Verhandlungen > 2021 > Dortmund