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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...
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| Lenguaje: | eng |
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2020
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| Acceso en línea: | http://cds.cern.ch/record/2744871 |