Boosting the efficiency of parametric detection with hierarchical neural networks is a research paper published in Physical review. D/Physical review. D. (2022). On theSindex it has a DataRank of 0. It has been cited 2 times.
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National Science Foundation
Grant: PHY-0757058
National Science Foundation
Grant: PHY-0823459
National Science Foundation
Grant: CCF-1740391
National Science Foundation
Grant: PHY-1911796
National Institutes of Health
Grant: 1G20RR030893-01
Core Research Computing Facility
New York State Empire State Development
Grant: C090171
National Science Foundation
Grant: 0757058
The Operation and Maintenance of the Laser Interferometer Gravitational Wave Observatory (LIGO)
National Science Foundation
Grant: 1740391
RAISE: Deep Gravitational Wave Exploration, Instrumental Insights and Noise Removal Through Machine Learning
National Science Foundation
Grant: 1911796
WOU-MMA: Shedding New Light on Buried Cosmic Accelerators with Gravitational Waves and High-Energy Neutrinos
National Science Foundation
Grant: 0823459
The Construction of the Advanced Laser Interferometer Gravitational Wave Observatory (AdvLIGO)
FWCI
0.29
Citation Percentile
0.6%
Citation Trend
Fields of Study
Keywords
Boosting the Efficiency of Parametric Detection with Hierarchical Neural Networks