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A New Deep-Neural-Network--Based Missing Transverse Momentum Estimator, and its Application to W Recoil
This dissertation presents the first Deep-Neural-Network–based missing transverse momentum ($p$$_{T}^{miss}$ estimator, called “DeepMET”. It utilizes all reconstructed particles in an event as input, and assigns an individual weight to each of them. The DeepMET estimator is the negative of the vecto...
Autor principal: | Feng, Yongbin |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2744871 |
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