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T 91: Machine Learning: Event and jet reconstruction
Freitag, 3. April 2020, 11:00–13:00, H-HS I
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11:00 |
T 91.1 |
Event reconstruction for ANTARES using Convolutional Neural Networks — •Nicole Geißelbrecht for the ANTARES-KM3NeT-Erlangen collaboration
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11:15 |
T 91.2 |
Adversarial Neural Network-based shape calibrations of observables for jet-tagging at CMS — Martin Erdmann, •Benjamin Fischer, Dennis Noll, Yannik Alexander Rath, Marcel Rieger, and David Josef Schmidt
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11:30 |
T 91.3 |
Study on the use of convolutional neural networks for strange-tagging based on jet images from calorimeters — •Nils J. Abicht, Johannes Erdmann, Olaf Nackenhorst, and Sonja Zeissner
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11:45 |
T 91.4 |
Di-tau mass reconstruction in ATLAS using regression-based deep neural networks — •Lena Herrmann, Philip Bechtle, Klaus Desch, Michael Hübner, and Peter Wagner
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12:00 |
T 91.5 |
Primary Vertex Reconstruction with ML in ACTS — •Bastian Schlag
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12:15 |
T 91.6 |
Track finding algorithm for the BelleII detector — •Thomas Lück and Thomas Kuhr for the Belle II collaboration
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12:30 |
T 91.7 |
Particle identification with the Belle II Calorimeter using Machine Learning — •Abtin Narimani Charan and Torben Ferber
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12:45 |
T 91.8 |
Muon bundle reconstruction with KM3NeT/ORCA using Deep Learning techniques — •Stefan Reck for the ANTARES-KM3NeT-Erlangen collaboration
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