Erlangen 2026 –
wissenschaftliches Programm
T 71: Data, AI, Computing, Electronics VII
Donnerstag, 19. März 2026, 16:15–18:00, KH 00.024
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16:15 |
T 71.1 |
Shapes are not enough: Preservattack and its use for finding vulnerabilities and uncertainties in machine learning applications — Philip Bechtle, Lucie Flek, Philipp Alexander Jung, Akbar Karimi, •Timo Saala, Alexander Schmidt, Matthias Schott, Philipp Soldin, Christopher Wiebusch, and Ulrich Willemsen
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16:30 |
T 71.2 |
Utilizing Adversarial Training for IceCube's Advanced Northern Track Selection — •Marco Zimmermann, Shuyang Deng, Lasse Düser, Philipp Soldin, Sönke Schwirn, and Christopher Wiebusch
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16:45 |
T 71.3 |
Investigating Robustness of Newtonian Noise Mitigation using Deep Learning at the Einstein Telescope — •Jan Kelleter, Markus Bachlechner, David Bertram, Johannes Erdmann, Patrick Schillings, and Achim Stahl
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17:00 |
T 71.4 |
A Machine-Learning based Topological Algorithm for the Level-1 Trigger System of CMS — •Lukas Ebeling, Johannes Haller, Artur Lobanov, and Matthias Schröder
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17:15 |
T 71.5 |
Finding Symbolic Representations of Graph Neural Networks used for Track Finding — •Urs Fischer, Sebastian Dittmeier, and Andre Schöning
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17:30 |
T 71.6 |
Symbolic Regression for the Extraction of Detector Response Formulas — •Johannes Merten and Johannes Erdmann
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17:45 |
T 71.7 |
Improving Machine-Learning-Driven Anomaly Detection for New Physics Searches at Belle II — •Gianni Di Paoli, David Giesegh, and Thomas Kuhr
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