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T 47: Neural networks and systematic uncertainties
Mittwoch, 1. April 2020, 16:30–19:00, H-HS IV
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16:30 |
T 47.1 |
VISPA: Platform as a Service (PaaS) for Scientific Data Analysis — Max Beer, Friederike Butt, Niclas Eich, Martin Erdmann, Peter Fackeldey, Benjamin Fischer, •Katharina Hafner, Dennis Noll, Yannik Rath, Erwin Rudi, Alexander Temme, and Maximilian Vieweg
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16:45 |
T 47.2 |
New methods for the application of neural networks in the presence of systematic uncertainties — Simon Jörger, Günter Quast, Roger Wolf, and •Stefan Wunsch
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17:00 |
T 47.3 |
Treating Uncertainties with Bayesian Neural Networks in a ttH Measurement — Ulrich Husemann, Philip Keicher, Matthias Schröder, and •Nikita Shadskiy
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17:15 |
T 47.4 |
Reduction of systematic uncertainties with adversarial neural networks in scope of the ttH(bb) analysis at CMS — •Simon Ehnle, Ulrich Husemann, Philip Keicher, Matthias Schröder, and Sebastian Wieland
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17:30 |
T 47.5 |
Runtime optimisation of Adversarial Neural Networks in the tW dilepton channel using the ATLAS detector — •Nicolas Boeing, Ian C. Brock, and Christian Kirfel
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17:45 |
T 47.6 |
Evaluation of performance gains in the training of neural networks for HEP analysis applications using GPUs — •Michael Holzbock, Günter Duckeck, and Klaus Dolag
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18:00 |
T 47.7 |
Use of Deep Learning techniques in the search for the Higgs boson decay to pair of charm quarks at CMS — Andrey Pozdnyakov, Xavier Coubez, Luca Mastrolorenzo, Spandal Mondal, Andrzej Novak, Alexander Schmidt, and •Guillermo Rocamora Pérez
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18:15 |
T 47.8 |
Reinforcement learning for sorting jets in top pair associated Higgs boson production — •Dennis Noll, Martin Erdmann, and Benjamin Fischer
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18:30 |
T 47.9 |
Multivariate analysis methods in the analysis of single top-quark production in association with a heavy boson at ATLAS — •Christian Kirfel, Ian Brock, Richard Baumann, and Piet Nogga
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18:45 |
T 47.10 |
Confronting EFT with artificial neural networks in the quest for physics beyond the Standard Model — Alexander Grohsjean and •Jonas Rübenach
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