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Machine-Learned Likelihood (MLL) is a method that, by combining modern machine-learning techniques with likelihood-based inference tests, allows estimating the experimental sensitivity of high-dimensional data sets. Here...

A search for new particles decaying into a pair of top quarks is performed using proton-proton collision data recorded with the ATLAS detector at the Large Hadron Collider at a center-of-mass energy of s=13  TeV corr...