SMuK 2023 –
scientific programme
T 63: ML Methods III
Wednesday, March 22, 2023, 15:50–17:20, HSZ/0405
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15:50 |
T 63.1 |
Automated Hyperparameter Optimization of Neural Networks for ATLAS analyses — •Erik Bachmann
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16:05 |
T 63.2 |
Optimising inference with binning — Phillip Keicher, Marcel Rieger, Peter Schleper, and •Jan Voss
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16:20 |
T 63.3 |
Uncertainty aware training — Markus Klute, •Artur Monsch, Günter Quast, Lars Sowa, and Roger Wolf
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16:35 |
T 63.4 |
Interpolating Antenna Calibration Data from Sparse Measurements with Information Field Theory — •Maximilian Straub, Martin Erdmann, and Alex Reuzki for the Pierre Auger collaboration
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16:50 |
T 63.5 |
Tau neutrino identification with Graph Neural Networks in KM3NeT/ORCA — •Lukas Hennig for the ANTARES-KM3NET-ERLANGEN collaboration
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17:05 |
T 63.6 |
Negative event weights in Machine Learning and search for heavy Higgs bosons in top quark pair events at CMS — •Jörn Bach, Christian Schwanenberger, Peer Stelldinger, and Alexander Grohsjean
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