Speaker
Sophia Vent
Description
Modern ML-based taggers have become the gold standard at the LHC, outperforming classical algorithms. Beyond pure efficiency, we also seek controllable and interpretable algorithms. We explore how we can move beyond black-box performance and toward physically meaningful understanding of modern taggers. Using explainable AI methods, we can connect tagger outputs with well-known physics observables. This allows us to describe the full discriminative power of a modern ML-based tagger with only three learned observables.
Authors
Ramon Winterhalder
(Università degli Studi di Milano)
Sophia Vent
Tilman Plehn
(Heidelberg University)