Toward real-time detection of unmodeled gravitational wave transients using convolutional neural networks

Authors

Institutions

Publication Details

Journal
Physical review. D/Physical review. D.
Published
2024-11-15
DOI
https://doi.org/10.1103/physrevd.110.104034
Citations
13
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
4.31

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Toward real-time detection of unmodeled gravitational wave transients using convolutional neural networks

M. R. Norman, V. Skliris, P. J. Sutton
13 citations
Physical review. D/Physical review. D.
Pulsars and Gravitational Waves Research
4.31
article

Toward real-time detection of unmodeled gravitational wave transients using convolutional neural networks

M. R. Norman, V. Skliris, P. J. Sutton
article en
13 citations

Abstract

No abstract available for this paper.
Physical review. D/Physical review. D.Vol. 110(10)
Cardiff University (GB)
National Science Foundation, Science and Technology Facilities Council
Openalex Percentile: Top 6%
Pulsars and Gravitational Waves Research
4.31
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Toward real-time detection of unmodeled gravitational wave transients using convolutional neural networks — M. R. Norman, V. Skliris, et al. · Physical review. D/Physical review. D. (2024) | TGRS Research Map | TGRS