3.5k citations · 6.6k across the 17 of their papers we have counts for
4 papers · 1 filter
Boosting the Efficiency of Parametric Detection with Hierarchical Neural Networks
Jingkai Yan, Robert Colgan, John Wright +3
Gravitational wave astronomy is a vibrant field that leverages both classic and modern data processing techniques for the understanding of the universe. Various approaches have bee…
Detecting and Diagnosing Terrestrial Gravitational-Wave Mimics Through Feature Learning
Robert E. Colgan, Zsuzsa Márka, Jingkai Yan +3
As engineered systems grow in complexity, there is an increasing need for automatic methods that can detect, diagnose, and even correct transient anomalies that inevitably arise an…
Generalized Approach to Matched Filtering using Neural Networks
Jingkai Yan, Mariam Avagyan, Robert E. Colgan +5
Gravitational wave science is a pioneering field with rapidly evolving data analysis methodology currently assimilating and inventing deep learning techniques. The bulk of the soph…
Efficient Gravitational-wave Glitch Identification from Environmental Data Through Machine Learning
Robert E. Colgan, K. Rainer Corley, Yenson Lau +4
The LIGO observatories detect gravitational waves through monitoring changes in the detectors' length down to below \, variation---a small fraction of the si…