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hep-ex2019
Bidirectional Long Short-Term Memory (BLSTM) neural networks for reconstruction of top-quark pair decay kinematics
Fardin Syed, Riccardo Di Sipio, Pekka Sinervo
A probabilistic reconstruction using machine-learning of the decay kinematics of top-quark pairs produced in high-energy proton-proton collisions is presented. A deep neural networ…
hep-ex2018
Eikos: a Bayesian unfolding method for differential cross-section measurements
Riccardo Di Sipio
A likelihood-based unfolding method based on Bayes' theorem is presented, with a particular emphasis on the application to differential cross-section measurements in high-energy pa…