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GWSkyNet. II. A Refined Machine-learning Pipeline for Real-time Classification of Public Gravitational Wave Alerts
Man Leong Chan
, Jess McIver
, Ashish Mahabal
, Cody Messick
, Daryl Haggard
, Nayyer Raza
, Yannick Lecoeuche
, Patrick J. Sutton
, Becca Ewing
, Francesco Di Renzo
, Miriam Cabero
, Raymond Ng
, Michael W. Coughlin
,
Shaon Ghosh
, Patrick Godwin
Physics and Astronomy
Research output
:
Contribution to journal
›
Article
›
peer-review
2
Scopus citations
Overview
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Dive into the research topics of 'GWSkyNet. II. A Refined Machine-learning Pipeline for Real-time Classification of Public Gravitational Wave Alerts'. Together they form a unique fingerprint.
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Keyphrases
Accurate Identification
20%
Astrophysical Signals
20%
Astrophysical Sources
20%
Astrophysical Transients
20%
Automatic pipeline
20%
Data Challenge
20%
Electromagnetic Follow-up
60%
False Alarm Rate
20%
Gravitational Wave Events
20%
Gravitational Waves
100%
KAGRA
40%
LIGO-Virgo
40%
Localization Information
40%
Low Latency
20%
Machine Learning Classifiers
20%
Machine Learning pipelines
100%
Masquerade
20%
Rapid Release
20%
Real-time Classification
100%
Sky Localization
40%
Computer Science
False Alarm Rate
50%
Learning System
100%
Machine Learning
100%
Physics
False Alarm
16%
Gravitational Wave
100%
Machine Learning
100%