Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz

AKPIK 3: Machine-learning methods and computing in astroparticle physics

Mittwoch, 27. März 2019, 16:00–17:50, H06

16:00 AKPIK 3.1 Exploring Optical Properties of Antarctic Ice with IceCube Using Gradient Descent — •Alexander Harnisch for the IceCube collaboration
16:10 AKPIK 3.2 Possible ways to improve the DeepCore NMO analysis — •Jan Weldert and Sebastian Böser for the IceCube collaboration
16:20 AKPIK 3.3 Using ANNs to Find Anomalies in Waveforms Detected by IceCube — •Max Pernklau for the IceCube collaboration
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
16:40 AKPIK 3.5 Search for new Source Populations with Autoencoding Neural Networks — •Simone Mender, Tobias Hoinka, and Kevin Schmidt
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
17:00 AKPIK 3.7 Towards online triggering for the radio detection of air showers using deep neural networks — •Florian Führer and Anne Zilles
17:10 AKPIK 3.8 German-Russian Astroparticle Data Life Cycle Initiative — •Victoria Tokareva for the KRAD/APPDS collaboration
17:20 AKPIK 3.9 Benchmarking of compute resources — •Benoit Roland, Felix Buehrer, Anton Gamel, and Markus Schumacher
17:30 AKPIK 3.10 Highly parallel CORSIKA processing — •Dominik Baack
17:40 AKPIK 3.11 Resistive Plate Chamber (RPC) tests as muon detector — •Victor Barbosa Martins, Vitor de Souza, Luis Lopes, and Sofia Andringa
100% | Bildschirmansicht | English Version | Kontakt/Impressum/Datenschutz
DPG-Physik > DPG-Verhandlungen > 2019 > Aachen