Convolutional neural network classifier for the output of the time-domain $\mathcal{F}$-statistic all-sky search for continuous gravitational waves-Reference-Cited by-同舟云学术

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Convolutional neural network classifier for the output of the time-domain $\mathcal{F}$-statistic all-sky search for continuous gravitational waves

Published:2020-06-23 Issue:2 Volume:1 Page:025016
ISSN:2632-2153
Container-title:Machine Learning: Science and Technology
language:
Short-container-title:Mach. Learn.: Sci. Technol.

Author:

Morawski Filip^ORCID,Bejger Michał^ORCID,Ciecieląg Paweł^ORCID

Funder

Narodowe Centrum Nauki

European Cooperation in Science and Technology

H2020 European Institute of Innovation and Technology

Publisher

IOP Publishing

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://iopscience.iop.org/article/10.1088/2632-2153/ab86c7/pdf

Reference49 articles.

1. Characterization of the LIGO detectors during their sixth science run

2. Advanced Virgo: a second-generation interferometric gravitational wave detector

3. Observation of Gravitational Waves from a Binary Black Hole Merger

4. GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Premerger detection of massive black hole binaries using deep learning;Physical Review D;2024-06-24

2. Mass and tidal parameter extraction from gravitational waves of binary neutron stars mergers using deep learning;Journal of Cosmology and Astroparticle Physics;2024-01-01

3. Novel neural-network architecture for continuous gravitational waves;Physical Review D;2023-09-18

4. Deep learning for intermittent gravitational wave signals;Physical Review D;2023-02-16

5. First machine learning gravitational-wave search mock data challenge;Physical Review D;2023-01-27

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