SMuK 2023 –
wissenschaftliches Programm
AKPIK 2: Applications in Particle and Astroparticle Physics
Dienstag, 21. März 2023, 17:00–19:00, ZEU/0118
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17:00 |
AKPIK 2.1 |
Studies of Machine Learning Inspired Clustering Algorithms for Jets — Amrita Bhattacherjee, Debarghya Ghoshdastidar, Stefan Kluth, and •Siddha Hill
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17:15 |
AKPIK 2.2 |
Providing GPU resources in a HEP analysis environment — Johannes Erdmann, Benjamin Fischer, Thomas Kreß, Dennis Noll, Andreas Nowack, and •Roman Suveyzdis
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17:30 |
AKPIK 2.3 |
Fast Columnar Physics Analyses of Terabyte-Scale LHC Data on a Cache-Aware Dask Cluster — Svenja Diekmann, Niclas Eich, Martin Erdmann, Peter Fackeldey, •Benjamin Fischer, Dennis Noll, and Yannik Rath
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17:45 |
AKPIK 2.4 |
ProGamer: PROgressively Growing Adversarial Modified (transformer-)Encoder Refinement — •Benno Käch, Isabell Melzer-Pellmann, and Dirk Krücker
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18:00 |
AKPIK 2.5 |
Machine Learning based defect detection for large-scale electrodes — •Sebastian Vetter
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18:15 |
AKPIK 2.6 |
Interpolation of Instrument Response Functions for the Cherenkov Telescope Array — •Rune Michael Dominik and Maximilian Linhoff for the CTA consortium
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18:30 |
AKPIK 2.7 |
Estimation of prediction uncertainties for data from Imaging Atmospheric Cherenkov Telescopes — •Cyrus Pan Walther and Maximilian Linhoff
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18:45 |
AKPIK 2.8 |
Testing Nested Machine Learning Models for the Cherenkov Telescope Array — •Lukas Beiske and Rune M. Dominik for the CTA collaboration
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