activity
20192023
most citedGravitational Wave Denoising of Binary Black Hole Mergers with Deep Learning

110 citations · 667 across the 12 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

gr-qc2020★ 70 cited

Accelerated, Scalable and Reproducible AI-driven Gravitational Wave Detection

E. A. Huerta, Asad Khan, Xiaobo Huang +10

The development of reusable artificial intelligence (AI) models for wider use and rigorous validation by the community promises to unlock new opportunities in multi-messenger astro…

gr-qc2020★ 28 cited

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…

gr-qc2020★ 51 cited

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…

gr-qc2020★ 49 cited

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…

physics.ins-det2020★ 108 cited

Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics

Dawit Belayneh, Federico Carminati, Amir Farbin +13

Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of particles produced i…