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Found 2 papers, 1 papers with code
Long Short-Term Memory (LSTM) networks with jet constituents for boosted top tagging at the LHC
Multivariate techniques based on engineered features have found wide adoption in the identification of jets resulting from hadronic top decays at the Large Hadron Collider (LHC).
Jet Constituents for Deep Neural Network Based Top Quark Tagging
Recent literature on deep neural networks for tagging of highly energetic jets resulting from top quark decays has focused on image based techniques or multivariate approaches using high-level jet substructure variables.
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