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Karlsruhe 2024 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 16: Data, AI, Computing 1 (anomaly detection)

Montag, 4. März 2024, 16:00–18:00, Geb. 30.33: MTI

16:00 T 16.1 Anomaly Detection Using Autoencoders in Belle II Data — •David Giesegh, Nikolai Hartmann, and Thomas Kuhr
16:15 T 16.2 VAE-based anomaly detection in dijet events at √s=13 TeV — •Aritra Bal, Benedikt Maier, Thea Aarrestad, Javier Duarte, Markus Klute, Jennifer Ngadiuba, Maurizio Pierini, Kinga Wozniak, and Irene Zoi
16:30 T 16.3 Deep neural network reconstruction of muon densities from measurements of the underground muon detector of the Pierre Auger Observatory — •Anton Poctarev for the Pierre-Auger collaboration
16:45 T 16.4 Neural network identification of highly inclined muons in water-Cherenkov particle detectors — •Mohsen Pourmohammad Shahvar for the Pierre-Auger collaboration
17:00 T 16.5 Nested Machine Learning Models for the Cherenkov Telescope ArrayLukas Beiske and •Maximilian Linhoff for the CTA collaboration
  17:15 T 16.6 The contribution has been withdrawn.
17:30 T 16.7 Machine-Learning-based Background Identification for the Radio Neutrino Observatory Greenland — •Philipp Laub for the RNO-G collaboration
17:45 T 16.8 ANNs for enhanced Pulse Shape Discrimination in GERDA — •Vikas Bothe
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