首页> Frontiers in big data> Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows.

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows.

导出 LinkOut

翻译打印收藏纠错

第一作者： Pratik,Jawahar

第一单位： Experimental Physics Department, European Center for Nuclear Research (CERN), Geneva, Switzerland.

作者： Pratik,Jawahar ^[1] ; Thea,Aarrestad ^[1] ; Nadezda,Chernyavskaya ^[1] ; Maurizio,Pierini ^[1] ; Kinga A,Wozniak ^[2] ; Jennifer,Ngadiuba ^[3] ; Javier,Duarte ^[4] ; Steven,Tsan ^[4]

作者单位： Experimental Physics Department, European Center for Nuclear Research (CERN), Geneva, Switzerland. ^[1] Experimental Physics Department, European Center for Nuclear Research (CERN), Geneva, Switzerland.;Faculty of Computer Science, University of Vienna, Vienna, Austria. ^[2] Particle Physics Division, Fermi National Accelerator Laboratory (FNAL), Batavia, IL, United States.;Lauritsen Laboratory of High Energy Physics, California Institute of Technology, Pasadena, CA, United States. ^[3] Department of Physics, University of California, San Diego, San Diego, CA, United States. ^[4]

关键词 Large Hadron Collider (LHC)anomaly detection (AD)convolutional neural net graph convolutional network (GCN)new physics beyond standard model normalizing flow (NF)variational auto encoder (VAE)

DOI 10.3389/fdata.2022.803685

PMID 35295683

发布时间 2024-09-29

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交

浏览0

Frontiers in big data

2022年5卷

803685页

相似文献

中文期刊
外文期刊
学位论文
会议论文

浏览0

点击下载本期目录封面

Frontiers in big data

2022年5卷

803685页

检索历史清除

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows.

Frontiers in big data

相似文献

同项目论文

Frontiers in big data

相关期刊

参考文献：
指定格式：	NoteExpress EndNote RefWorks NoteFirst

检索历史 清除

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows.

Frontiers in big data

相似文献

同项目论文

Frontiers in big data

相关期刊

检索历史清除