Local Diagnostics of Learned Event Representations for Anomaly Detection at the HL-LHC
Anomaly detection, the identification of collision events that deviate from Standard Model expectations, is one of the most promising model-agnostic strategies for new-physics searches at the Large Hadron Collider. Searching for rare events in learned low-dimensional representations removes the need to commit to hand-c...
D. Genovese, Philip Ploner, Simone Scardapane et al.
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