Deep generative models for fast shower simulation in ATLAS

被引：12

作者：

Salamani, Dalila ^{[1
]}

Gadatsch, Stefan ^{[1
]}

Golling, Tobias ^{[1
]}

Stewart, Graeme Andrew ^{[2
]}

Ghosh, Aishik ^{[3
]}

Rousseau, David ^{[3
]}

Hasib, Ahmed ^{[4
]}

Schaarschmidt, Jana ^{[5
]}

机构：

[1] Univ Geneva, Geneva, Switzerland

[2] CERN, Geneva, Switzerland

[3] LAL, Bures Sur Yvette, France

[4] Univ Edinburgh, Edinburgh, Midlothian, Scotland

[5] Univ Washington, Seattle, WA 98195 USA

来源：

2018 IEEE 14TH INTERNATIONAL CONFERENCE ON E-SCIENCE (E-SCIENCE 2018) | 2018年

关键词：

High Energy Physics; Fast simulation; Deep Neural Networks; Generative Models; VAE; GAN;

D O I：

10.1109/eScience.2018.00091

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

引用

下载

页码：348 / 348

页数：1

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