SMuK 2023 –
wissenschaftliches Programm
T 86: ML Methods IV
Mittwoch, 22. März 2023, 17:30–19:00, HSZ/0405
![](/static/ip/plus.gif) |
17:30 |
T 86.1 |
EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets — •Erik Buhmann
|
|
|
![](/static/ip/plus.gif) |
17:45 |
T 86.2 |
Development of novel machine learning algorithms for robust jet flavour classification for Run3 at CMS — •Annika Stein, Judith Bennertz, Xavier Coubez, Alexander Jung, Summer Kassem, Ming-Yan Lee, Spandan Mondal, Alexandre de Moor, Andrzej Novak, Alexander Schmidt, and Hendrik Schönen
|
|
|
![](/static/ip/plus.gif) |
18:00 |
T 86.3 |
Deep Neural Networks for jet-flavor tagging based on different hadronization models — •Aritra Bal, Markus Klute, and Roger Wolf
|
|
|
![](/static/ip/plus.gif) |
18:15 |
T 86.4 |
Multi-parameter Conditioning of Generative Models for Fast Simulation of Highly Granular Calorimeter Showers — •Peter McKeown
|
|
|
![](/static/ip/plus.gif) |
18:30 |
T 86.5 |
Super-resolution of photon calorimeter images using generative adversarial networks — Johannes Erdmann, Aaron van der Graaf, •Florian Mausolf, and Olaf Nackenhorst
|
|
|
![](/static/ip/plus.gif) |
18:45 |
T 86.6 |
Generative Modeling with Diffusion Neural Networks for Fast Simulation of Electromagnetic Showers in the International Large Detector — •Anatolii Korol
|
|
|