Deep Learning for Gravitational-Wave Data Analysis: A Resampling White-Box Approach

Deep Learning for Gravitational-Wave Data Analysis: A Resampling White-Box Approach

In this work, we apply Convolutional Neural Networks (CNNs) to detect gravitational wave (GW) signals of compact binary coalescences, using single-interferometer data from real LIGO detectors. Here, we adopted a resampling white-box approach to advance towards a statistical understanding of uncertai...

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Bibliographic Details
Main Authors: Manuel D. Morales, Javier M. Antelis, Claudia Moreno, Alexander I. Nesterov
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Sensors
Subjects:
gravitational waves
Deep Learning
convolutional neural networks
binary black holes
LIGO detectors
probabilistic binary classification
Online Access:https://www.mdpi.com/1424-8220/21/9/3174

Internet

https://www.mdpi.com/1424-8220/21/9/3174

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