IN2P3/IRFU Machine Learning workshop

Search for New Physics using semi-supervised ML techniques

23 janv. 2020, 11:45

25m

Amphi (CC-IN2P3)

ML for analysis : Application of Machine Learning to analysis, event classification and fundamental parameters inference

Orateurs

Julien Donini (UBP/LPC/IN2P3) Louis Vaslin (LPC Clermont) Ioan Dinu (INFIN-HH / LPC)

Description

Preliminary studies for model-independent search for new physics at the LHC will be presented in the context of anomaly detection by training semi-supervised methods (e.g. autoencoders). The use-case of a search for a dijet resonance on a QCD background will be considered using toy datasets (Delphes sample and the LHC Olympics 2020 data).

Documents de présentation

ML-ccin2p3-230120.pdf