110 citations · 667 across the 12 of their papers we have counts for
5 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…
Deep Transfer Learning for Star Cluster Classification: I. Application to the PHANGS-HST Survey
Wei Wei, E. A. Huerta, Bradley C. Whitmore +13
We present the results of a proof-of-concept experiment which demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters…
XSP: Across-Stack Profiling and Analysis of Machine Learning Models on GPUs
Cheng Li, Abdul Dakkak, Jinjun Xiong +3
There has been a rapid proliferation of machine learning/deep learning (ML) models and wide adoption of them in many application domains. This has made profiling and characterizati…
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…
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…