T 67: Data, AI, Computing 5 (normalising flows)
Wednesday, March 6, 2024, 16:00–17:45, Geb. 30.33: MTI
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16:00 |
T 67.1 |
Applications of Normalizing Flows in High-Energy Particle Physics — •Lars Sowa, Roger Wolf, Markus Klute, and Günter Quast
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16:15 |
T 67.2 |
Parameter reconstruction for gravitational wave signals at the Einstein Telescope using conditional normalizing flows — Johannes Erdmann and •Tobias Reike
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16:30 |
T 67.3 |
Normalizing Flows to Infer Ultra-High-Energy Cosmic-Ray Source Properties from Surface Detector Measurements at the Pierre Auger Observatory — •Frederik Krieger, Teresa Bister, Martin Erdmann, and Josina Schulte
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16:45 |
T 67.4 |
Using neural networks to calculate bounce actions — •Fabio Campello, Georg Weiglein, and Thomas Biekötter
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17:00 |
T 67.5 |
Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows — •Thorsten Buss
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17:15 |
T 67.6 |
Improving MCMC sampling efficiency with normalizing flows — Michael Dudkowiak, Cornelius Grunwald, Oliver Schulz, and •Willy Weber
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17:30 |
T 67.7 |
Conditional normalizing flows for correcting simulations — •Caio Cesar Daumann, Mauro Donega, Johannes Erdmann, Massimiliano Galli, Jan Lukas Späh, and Davide Valsecchi
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