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Aachen 2019 – scientific programme

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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz

AKPIK 2: Machine-learning methods and computing in particle physics

Tuesday, March 26, 2019, 16:00–17:50, H10

16:00 AKPIK 2.1 Pixel detector background simulation using generative adversarial networks at Belle II — •Matej Srebre
16:10 AKPIK 2.2 Photon position reconstruction using Machine Learning with the Belle II electromagnetic calorimeter — •Yu Hu
16:20 AKPIK 2.3 Analysis of GERDA detector surface events with deep learning algorithms — •Péter Kicsiny for the GERDA collaboration
16:30 AKPIK 2.4 Learning to rank Higgs-Boson candidatesLukas Pensel, Alexander Segner, •Marius Köppel, Martin Wagener, Andreas Karwath, Christian Schmitt, and Stefan Kramer
16:40 AKPIK 2.5 Refining the EXO-200 detector simulation using GANs — •Federico Bontempo, Johannes Link, Tobias Ziegler, Gisela Anton, and Thilo Michel
16:50 AKPIK 2.6 Event reconstruction in EXO-200 using Deep Learning — •Johannes Link, Federico Bontempo, Tobias Ziegler, Gisela Anton, and Thilo Michel
17:00 AKPIK 2.7 Circuit Synthesis of the Kuramoto Model and Electrical Interpretation of its Synchronization ConditionKarlheinz Ochs, •Dennis Michaelis, Julian Roggendorf, Petro Feketa, Alexander Schaum, and Thomas Meuerer
17:10 AKPIK 2.8 HfO2-based Memristive Navigation ProcessorKarlheinz Ochs, •Enver Solan, Dennis Michaelis, and Leonard Hilgers
17:20 AKPIK 2.9 Universal Self-Organizing Logic Gates: A Wave Digital EmulationKarlheinz Ochs, •Enver Solan, Dennis Michaelis, and Leon Schmitz
17:30 AKPIK 2.10 Solving the Np-complete Subset Sum Problem with an Electrical Circuit Using Physical Memristor ModelsKarlheinz Ochs, Enver Solan, •Dennis Michaelis, and Maximilian Herbrechter
17:40 AKPIK 2.11 Was ist Geometrische Algebra? Auf dem Weg zu einer modernen Mathematikausbildung in der Ingenieurinformatik — •Martin Erik Horn
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