Aachen 2019 –
wissenschaftliches Programm
AKPIK 3: Machine-learning methods and computing in astroparticle physics
Mittwoch, 27. März 2019, 16:00–17:50, H06
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16:00 |
AKPIK 3.1 |
Exploring Optical Properties of Antarctic Ice with IceCube Using Gradient Descent — •Alexander Harnisch for the IceCube collaboration
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16:10 |
AKPIK 3.2 |
Possible ways to improve the DeepCore NMO analysis — •Jan Weldert and Sebastian Böser for the IceCube collaboration
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16:20 |
AKPIK 3.3 |
Using ANNs to Find Anomalies in Waveforms Detected by IceCube — •Max Pernklau for the IceCube collaboration
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16:30 |
AKPIK 3.4 |
Determination of Antarctic Ice Parameters Using a Neural Network — •Sebastian Bange, Mirco Hünnefeld, and Alexander Harnisch for the IceCube collaboration
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16:40 |
AKPIK 3.5 |
Search for new Source Populations with Autoencoding Neural Networks — •Simone Mender, Tobias Hoinka, and Kevin Schmidt
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16:50 |
AKPIK 3.6 |
Cascade Reconstruction in IceCube using Generative Neural Networks — •Mirco Huennefeld, Tobias Hoinka, Jan Soedingrekso, Sebastian Bange, and Alexander Harnisch for the IceCube collaboration
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17:00 |
AKPIK 3.7 |
Towards online triggering for the radio detection of air showers using deep neural networks — •Florian Führer and Anne Zilles
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17:10 |
AKPIK 3.8 |
German-Russian Astroparticle Data Life Cycle Initiative — •Victoria Tokareva for the KRAD/APPDS collaboration
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17:20 |
AKPIK 3.9 |
Benchmarking of compute resources — •Benoit Roland, Felix Buehrer, Anton Gamel, and Markus Schumacher
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17:30 |
AKPIK 3.10 |
Highly parallel CORSIKA processing — •Dominik Baack
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17:40 |
AKPIK 3.11 |
Resistive Plate Chamber (RPC) tests as muon detector — •Victor Barbosa Martins, Vitor de Souza, Luis Lopes, and Sofia Andringa
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