85 citations · 197 across the 4 of their papers we have counts for
5 papers · 1 filter
Deep Learning with Quantized Neural Networks for Gravitational Wave Forecasting of Eccentric Compact Binary Coalescence
Wei Wei, E. A. Huerta, Mengshen Yun +5
We present the first application of deep learning forecasting for binary neutron stars, neutron star - black hole systems, and binary black hole mergers that span an eccentricity r…
Deep Learning Ensemble for Real-time Gravitational Wave Detection of Spinning Binary Black Hole Mergers
Wei Wei, Asad Khan, E. A. Huerta +2
We introduce the use of deep learning ensembles for real-time, gravitational wave detection of spinning binary black hole mergers. This analysis consists of training independent ne…
Deep learning for gravitational wave forecasting of neutron star mergers
Wei Wei, E. A. Huerta
We introduce deep learning time-series forecasting for gravitational wave detection of binary neutron star mergers. This method enables the identification of these signals in real…
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…
Gravitational Wave Denoising of Binary Black Hole Mergers with Deep Learning
Wei Wei, E. A. Huerta
Gravitational wave detection requires an in-depth understanding of the physical properties of gravitational wave signals, and the noise from which they are extracted. Understanding…