SMuK 2023 –
wissenschaftliches Programm
T 103: AI Topical Day – Simulation, Inverse Problems and Algorithmic Development (joint session AKPIK/T)
Donnerstag, 23. März 2023, 15:45–17:15, HSZ/0004
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15:45 |
T 103.1 |
Efficient Sampling from Differentiable Matrix Elements with Normalizing Flows — •Annalena Kofler, Vincent Stimper, Mikhail Mikhasenko, Michael Kagan, and Lukas Heinrich
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16:00 |
T 103.2 |
Generating Accurate Showers in Highly Granular Calorimeters Using Normalizing Flows — •Thorsten Buss
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16:15 |
T 103.3 |
Introspection for a normalizing-flow-based recoil calibration — •Lars Sowa, Jost von den Driesch, Roger Wolf, Markus Klute, and Günter Quast
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16:30 |
T 103.4 |
The contribution has been withdrawn.
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16:45 |
T 103.5 |
A method for inferring signal strength modifiers by conditional invertible neural networks — •Mate Zoltan Farkas, Svenja Diekmann, Niclas Eich, and Martin Erdmann
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17:00 |
T 103.6 |
Reconstruction of SAXS Data using Invertible Neural Networks — •Erik Thiessenhusen, Melanie Rödel, Thomas Kluge, Michael Bussmann, Thomas Cowan, and Nico Hoffmann
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