T 53: Data Analysis, Information Technology and Artificial Intelligence 3
Dienstag, 22. März 2022, 16:15–18:30, T-H38
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16:15 |
T 53.1 |
Improved selective background Monte Carlo simulation at Belle II with graph attention networks and weighted events — •Boyang Yu, Nikolai Hartmann, and Thomas Kuhr
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16:30 |
T 53.2 |
Analysis Specific Filters for Selective Background Monte Carlo Simulations at Belle II — •Luca Schinnerl, Boyang Yu, Nikolai Hartmann, and Thomas Kuhr
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16:45 |
T 53.3 |
The contribution has been moved to ST 3.6.
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17:00 |
T 53.4 |
Progressive Generative Adversarial Networks for High Energy Physics Calorimeter Simulations — •Simon Schnake, Kerstin Borras, Dirk Krücker, Florian Rehm, and Sofia Vallecorsa
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17:15 |
T 53.5 |
Angular Conditioning of Generative Models for Fast Calorimeter Shower Simulation — •Peter McKeown
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17:30 |
T 53.6 |
Deep Set Generation of Collider Events — •Erik Buhmann
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17:45 |
T 53.7 |
Generative Models For Hadron Shower Simulation — •Engin Eren
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18:00 |
T 53.8 |
Refinement of jet simulation with generative adversarial networks — •Shruthi Janardhan, Sven Harder, Patrick Connor, Peter Schleper, Daniel Ruprecht, and Sebastian Götschel
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18:15 |
T 53.9 |
Using ML to analytically model the CMS detector response to jets — •Nils Gerber, Samuel Bein, and Peter Schleper
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