178 citations · 537 across the 11 of their papers we have counts for
4 papers · 1 filter
Enabling real-time multi-messenger astrophysics discoveries with deep learning
E. A. Huerta, Gabrielle Allen, Igor Andreoni +57
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that…
Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-Encoders
Hongyu Shen, Daniel George, E. A. Huerta +1
Denoising of time domain data is a crucial task for many applications such as communication, translation, virtual assistants etc. For this task, a combination of a recurrent neural…
Statistically-informed deep learning for gravitational wave parameter estimation
Hongyu Shen, E. A. Huerta, Eamonn O'Shea +2
We introduce deep learning models to estimate the masses of the binary components of black hole mergers, , and three astrophysical properties of the post-merger compact…
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era
Gabrielle Allen, Igor Andreoni, Etienne Bachelet +45
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrop…