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Würzburg 2018 – scientific programme

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T: Fachverband Teilchenphysik

T 87: Datenanalyse

Thursday, March 22, 2018, 16:30–19:00, Z6 - SR 2.005

16:30 T 87.1 Adversarial networks used in a single-top-quark analysis in ATLAS — •Rui Zhang and Ian C. Brock
16:45 T 87.2 Modernized track reconstruction in ATLAS with the ACTS software project — •Paul Gessinger, Andreas Salzburger, and Stefan Tapprogge
17:00 T 87.3 Deep Learning mit unbalancierten Datensätzen — •Stefan Geißelsöder für die ANTARES-KM3NeT-Erlangen Kollaboration
17:15 T 87.4 Distributed make-like Analyses on the Grid based on Spotify's Pipelining Package luigi — •Marcel Rieger, Martin Erdmann, Benjamin Fischer, and Ralf Florian von Cube
17:30 T 87.5 KM3NeT/ORCA data analysis using unsupervised Deep Learning — •Stefan Reck for the ANTARES-KM3NeT-Erlangen collaboration
17:45 T 87.6 Jet-Rekonstruktion mit neuronalen Netzen im ATLAS Level-1 Kalorimeter Trigger — •Bastian Schlag, Volker Büscher, Christian Schmitt, Stefan Kramer und Andreas Karwath
  18:00 T 87.7 The contribution has been withdrawn.
18:15 T 87.8 Studies for Top Quark Reconstruction with Deep Learning — •Tim Kallage, Johannes Erdmann, Olaf Nackenhorst, and Kevin Kröninger
18:30 T 87.9 Jet-Klassifizierung mithilfe von „domain adaption“ in tiefen künstlichen neuronalen NetzenMatthias Mozer, Thomas Müller und •David Walter
18:45 T 87.10 Tau neutrino appearance studies with KM3NeT-ORCA using Deep Learning techniques — •Michael Moser for the ANTARES-KM3NeT-Erlangen collaboration
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