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11/26/2019
Enabling real-time multi-messenger astrophysics discoveries with deep learning
Multi-messenger astrophysics is a fast-growing, interdisciplinary field ...
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03/06/2019
Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-Encoders
Denoising of time domain data is a crucial task for many applications su...
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02/01/2019
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era
This report provides an overview of recent work that harnesses the Big D...
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05/07/2018
Real-time regression analysis with deep convolutional neural networks
We discuss the development of novel deep learning algorithms to enable r...
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11/27/2017
Denoising Gravitational Waves using Deep Learning with Recurrent Denoising Autoencoders
Gravitational wave astronomy is a rapidly growing field of modern astrop...
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11/21/2017
Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation with LIGO Data
The recent Nobel-prize-winning detections of gravitational waves from me...
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11/20/2017
Glitch Classification and Clustering for LIGO with Deep Transfer Learning
The detection of gravitational waves with LIGO and Virgo requires a deta...
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11/16/2017
Eccentric, nonspinning, inspiral, Gaussian-process merger approximant for the detection and characterization of eccentric binary black hole mergers
We present ENIGMA, a time domain, inspiral-merger-ringdown waveform mode...
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11/16/2017
ENIGMA: Eccentric, Non-spinning, Inspiral Gaussian-process Merger Approximant for the characterization of eccentric binary black hole mergers
We present ENIGMA, a time domain, inspiral-merger-ringdown waveform mode...
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11/08/2017
Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation: Results with Advanced LIGO Data
The recent Nobel-prize-winning detections of gravitational waves from me...
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06/22/2017