recid:2802038 - Search Results - CERN Document Server

Search collections:

Sort by:	Display results:	Output format:

CERN Document Server	1 records found	Search took 0.92 seconds.

Maximum likelihood reconstruction of water Cherenkov events with deep generative neural networks / Jia, Mo (SUNY, Stony Brook) ; Kumar, Karan (SUNY, Stony Brook) ; Mackey, Liam S. (Rensselaer Poly.) ; Putra, Alexander (BMCC, New York) ; Vilela, Cristovao (CERN) ; Wilking, Michael J. (SUNY, Stony Brook) ; Xia, Junjie (Kamioka Observ.) ; Yanagisawa, Chiaki (SUNY, Stony Brook ; BMCC, New York) ; Yang, Karan (Cornell U., CIS)
Large water Cherenkov detectors have shaped our current knowledge of neutrino physics and nucleon decay, and will continue to do so in the foreseeable future. These highly capable detectors allow for directional and topological, as well as calorimetric information to be extracted from signals on their photosensors. [...]
arXiv:2202.01276.- 2022-06-17 - 20 p. - Published in : Front. Big Data 5 (2022) 868333 Fulltext: 2202.01276 - PDF; Publication - PDF;

Detailed record

Interested in being notified about new results for this query?
Set up a personal email alert or subscribe to the RSS feed.

Haven't found what you were looking for? Try your search on other servers:
recid:2802038 in Amazon recid:2802038 in CERN EDMS recid:2802038 in CERN Intranet recid:2802038 in CiteSeer recid:2802038 in Google Books recid:2802038 in Google Scholar recid:2802038 in Google Web recid:2802038 in IEC	recid:2802038 in IHS recid:2802038 in INSPIRE recid:2802038 in ISO recid:2802038 in KISS Books/Journals recid:2802038 in KISS Preprints recid:2802038 in NEBIS recid:2802038 in SLAC Library Catalog

CERN Document Server

Access articles, reports and multimedia content in HEP

Main menu

CERN Accelerating science