CapsNets continuing the convolutional quest
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 backgr...
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| Format: | Article |
| Language: | English |
| Published: |
SciPost
2020-02-01
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| Series: | SciPost Physics |
| Online Access: | https://scipost.org/SciPostPhys.8.2.023 |
| Summary: | 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. |
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| ISSN: | 2542-4653 |