3 papers
hep-ph2025
Simulation-Prior Independent Neural Unfolding Procedure
Anja Butter, Theo Heimel, Nathan Huetsch +2
Machine learning allows unfolding high-dimensional spaces without binning at the LHC. The new SPINUP method extracts the unfolded distribution based on a neural network encoding th…
hep-ph2025
How to Unfold Top Decays
Luigi Favaro, Roman Kogler, Alexander Paasch +3
Using unfolded top-quark decay data we can measure the top quark mass, as well as search for unexpected kinematic effects. We present a new generative unfolding method for the two…
hep-ph2024
Generative Unfolding with Distribution Mapping
Anja Butter, Sascha Diefenbacher, Nathan Huetsch +4
Machine learning enables unbinned, highly-differential cross section measurements. A recent idea uses generative models to morph a starting simulation into the unfolded data. We sh…