Master Thesis Open Access
Sowa, Lars
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"name": "Sowa, Lars"
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"description": "<p>The SuperKEKB collider in Japan accelerates<br>\nelectrons and positrons which collide at an energy of 11 GeV aiming to produce B meson<br>\npairs. To analyse the properties of a B meson, it gets recombined from its decay daughters.<br>\nSince there are a lot of background events that mimic the signature of a B meson, it is<br>\nimportant to suppress these events. Such a suppression is called Continuum Suppression. This work aims to further improve the Deep Continuum Suppression, which is perfromed by a Multilayer Perceptron (MLP), by three points: Firstly, an MLP needs a fixed order for input particles. Therefore, this thesis<br>\npresents a reliable, self-attention-based input mechanism which allows for invariance under<br>\nthe particle order. Secondly, to guarantee certainty about the prediction of deep learning models, there is a<br>\nhigh interest in models with predictive uncertainties. This is addressed using the concept<br>\nof Deep Ensembles to predict uncertainties of continuum classifications.<br>\nFinally, the use of vertex information for the training of a model leads to a bias in<br>\ncertain analysis variables. Since this could lead to falsification of further studies, a Distance<br>\nCorrelation is used to decorrelate the Continuum Suppression model from third variables.</p>",
"keywords": [
"Continuum Suppression",
"Deep Learning",
"Uncertainties",
"Decorrelation",
"Self-Attention"
],
"language": "eng",
"publication_date": "2021-07-27",
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"title": "Master Thesis",
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"report_number": "ETP-KA/2021-09",
"supervisors": [
{
"affiliation": "KIT/SCC",
"name": "Kahn, James"
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{
"affiliation": "KIT/ETP",
"name": "Goldenzweig, Pablo"
},
{
"affiliation": "KIT/ETP",
"name": "Husemann, Ulrich"
},
{
"affiliation": "KIT/ETP",
"name": "Quast, G\u00fcnter"
}
]
},
"title": "Deep Continuum Suppression with Predictive Uncertainties at the Belle II Experiment"
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75
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