Conveners
Computing: Machine Learning
- Paul Glaysher (DESY)
- Yannik Rath (RWTH Aachen University)
Computing
- Christoph Wissing (DESY)
- Rene Caspart (KIT - Karlsruhe Institute of Technology (DE))
José Manuel Clavijo Columbié
(DESY)
26/11/2019, 14:25
The ATLAS ttH(bb) analysis is limited by the background modelling uncertainties, that result in a bias of the classifier towards the Monte Carlo generator used for training. We apply adversarial domain adaptation to train a more generic classifier. We employ a neural network that simultaneously classifies the signal versus background events, while minimizing the difference of the classifier...
Mr
Steffen Korn
(II Physikalisches Institut, Georg-August-Universität Göttingen)
26/11/2019, 14:45
Through the associated production of the ttgamma process the strength of the electromagnetic gauge coupling of the top quark and the photon can be measured. The measurement of this fundamental parameter of the Standard Model (SM) also serves as a test of the vector structure of the electromagnetic interaction and a probe to new physics beyond the SM such as potential tensor contributions....
Tobias Lösche
(University of Hamburg)
26/11/2019, 15:10
A precise determination of the interactions of the Higgs boson with other SM particles is a crucial part of the LHC physics program. When determining the top Yukawa coupling in ttH(bb) events, deep learning plays an integral role. In the single-lepton channel, multivariate approaches using deep neural networks (DNNs) achieve state-of-the-art performance in signal/background...
