The new nonclosure loss term, made differentiable with a sigmoid approximation, lets the neural network optimize the ABCD background estimate directly, improving closure and training stability.
Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at √s=13 TeV
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Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC
The new nonclosure loss term, made differentiable with a sigmoid approximation, lets the neural network optimize the ABCD background estimate directly, improving closure and training stability.