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arXiv · 2008.06545

GANplifying Event Samples

Anja Butter·Sascha Diefenbacher·Gregor Kasieczka·Benjamin Nachman·Tilman Plehn
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Abstract

A critical question concerning generative networks applied to event generation in particle physics is if the generated events add statistical precision beyond the training sample. We show for a simple example with increasing dimensionality how generative networks indeed amplify the training statistics. We quantify their impact through an amplification factor or equivalent numbers of sampled events.

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Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, Benjamin Nachman, Tilman Plehn. 2020-08-14. GANplifying Event Samples. https://doi.org/10.21468/scipostphys.10.6.139

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