Trials factor for semi-supervised NN classifiers in searches for narrow resonances at the LHC
To mitigate the model dependencies of searches for new narrow resonances at the Large Hadron Collider (LHC), semi-supervised Neural Networks (NNs) can be used. Unlike fully supervised classifiers these models introduce an additional look-elsewhere effect in the process of optimising thresholds on th...
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
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SciPost
2024-11-01
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| Saila: | SciPost Physics Core |
| Sarrera elektronikoa: | https://scipost.org/SciPostPhysCore.7.4.073 |
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