30 citations · 179 across the 19 of their papers we have counts for
3 papers · 1 filter
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…
The Physics Behind ML-based Quark-Gluon Taggers
Sophia Vent, Ramon Winterhalder, Tilman Plehn
Jet taggers provide an ideal testbed for applying explainability techniques to powerful ML tools. For theoretically and experimentally challenging quark-gluon tagging, we first ide…
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…