Speaker
Bernd Bruegmann
Description
Gravitational wave data analysis solves a specific problem in signal analysis for time-series data with noise. Recently (starting 2017), deep learning methods have been applied to different aspects of the problem, in particular noise classification, signal detection, denoising, and parameter estimation. We discuss briefly how certain convolutional and recurrent networks work in this context. Results from first experiments with such techniques on mock signals are presented.
