Die DPG-Frühjahrstagung in Bonn musste abgesagt werden! Lesen Sie mehr ...
T 5: Machine Learning: QCD and electromagnetic showers
Montag, 30. März 2020, 16:30–18:00, H-HS III
 |
16:30 |
T 5.1 |
Deep Learning-based Air-Shower Reconstruction at the Pierre Auger Observatory — Martin Erdmann, •Jonas Glombitza, and Alexander Temme for the Pierre Auger collaboration
|
|
|
|
16:45 |
T 5.2 |
Simulation of Extensive Air Showers with Deep Neural Networks — Steffen Hahn, •Marcel Köpke, and Markus Roth
|
|
|
|
17:00 |
T 5.3 |
Generative Models for Fast Shower Simulation — •Sascha Diefenbacher, Erik Buhmann, Engin Eren, Frank Gaede, and Gregor Kasieczka
|
|
|
|
17:15 |
T 5.4 |
Understanding Generative Neural Networks for Fast Simulation of High-Granular Calorimeters — •Erik Buhmann, Gregor Kasieczka, Sascha Diefenbacher, Engin Eren, and Frank Gaede
|
|
|
|
17:30 |
T 5.5 |
Studies on using Generative Adversarial Networks to simulate parton showers — Johannes Erdmann, •Alexander Froch, and Olaf Nackenhorst
|
|
|
|
17:45 |
T 5.6 |
Towards a Data-Driven Simulation of QCD Radiation with Generative Models — André Schöning, •Christof Sauer, and Danilo Enoque Ferreira de Lima
|
|
|