2 papers
hep-ex2025
Anomaly preserving contrastive neural embeddings for end-to-end model-independent searches at the LHC
Kyle Metzger, Lana Xu, Mia Sodini +4
Anomaly detection - identifying deviations from Standard Model predictions - is a key challenge at the Large Hadron Collider due to the size and complexity of its datasets. This is…
hep-ex2025
Robust resonant anomaly detection with NPLM
Gaia Grosso, Debajyoti Sengupta, Tobias Golling +1
In this study, we investigate the application of the New Physics Learning Machine (NPLM) algorithm as an alternative to the standard CWoLa method with Boosted Decision Trees (BDTs)…