CapsNets continuing the convolutional quest
Sascha Diefenbacher, Hermann Frost, Gregor Kasieczka, Tilman Plehn, Jennifer M. Thompson
SciPost Phys. 8, 023 (2020) · published 7 February 2020
- doi: 10.21468/SciPostPhys.8.2.023
- Submissions/Reports
Abstract
Capsule networks are ideal tools to combine event-level and subjet information at the LHC. After benchmarking our capsule network against standard convolutional networks, we show how multi-class capsules extract a resonance decaying to top quarks from both, QCD di-jet and the top continuum backgrounds. We then show how its results can be easily interpreted. Finally, we use associated top-Higgs production to demonstrate that capsule networks can work on overlaying images to go beyond calorimeter information.
Cited by 18
Authors / Affiliations: mappings to Contributors and Organizations
See all Organizations.- 1 Sascha Diefenbacher,
- 2 Hermann Frost,
- 2 Gregor Kasieczka,
- 1 Tilman Plehn,
- 1 Jennifer Thompson
- 1 Ruprecht-Karls-Universität Heidelberg / Heidelberg University
- 2 Universität Hamburg / University of Hamburg [UH]
Funders for the research work leading to this publication