DeepMET is a neural-network-based missing transverse momentum estimator that improves resolution by 10-30% over existing CMS methods across a range of final states.
Pileup-per-particle identification: optimisation for Run 2 Legacy and beyond
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
hep-ex 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
DeepMET: Improving missing transverse momentum estimation with a deep neural network
DeepMET is a neural-network-based missing transverse momentum estimator that improves resolution by 10-30% over existing CMS methods across a range of final states.