3 citations · 8 across the 11 of their papers we have counts for
4 papers · 1 filter
Detecting the Undetected: Overcoming Biases in Gravitational-Wave Population Studies
Ryan Raikman, Simone Bavera, Tassos Fragos
In the flourishing field of gravitational-wave astronomy, accurately inferring binary black hole merger formation channels is paramount. The Bayesian hierarchical model selection a…
GWAK: Gravitational-Wave Anomalous Knowledge with Recurrent Autoencoders
Ryan Raikman, Eric A. Moreno, Ekaterina Govorkova +10
Matched-filtering detection techniques for gravitational-wave (GW) signals in ground-based interferometers rely on having well-modeled templates of the GW emission. Such techniques…
Demonstration of Machine Learning-assisted real-time noise regression in gravitational wave detectors
Muhammed Saleem, Alec Gunny, Chia-Jui Chou +17
Real-time noise regression algorithms are crucial for maximizing the science outcomes of the LIGO, Virgo, and KAGRA gravitational-wave detectors. This includes improvements in the…
Applications of Deep Learning to physics workflows
Manan Agarwal, Jay Alameda, Jeroen Audenaert +65
Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing…