3 papers
astro-ph.IM2020
Physically constrained causal noise models for high-contrast imaging of exoplanets
Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz +1
The detection of exoplanets in high-contrast imaging (HCI) data hinges on post-processing methods to remove spurious light from the host star. So far, existing methods for this tas…
astro-ph.HE2020
Enhancing Gravitational-Wave Science with Machine Learning
Elena Cuoco, Jade Powell, Marco Cavaglià +23
Machine learning has emerged as a popular and powerful approach for solving problems in astrophysics. We review applications of machine learning techniques for the analysis of grou…
astro-ph.IM2019
Convolutional neural networks: a magic bullet for gravitational-wave detection?
Timothy D. Gebhard, Niki Kilbertus, Ian Harry +1
In the last few years, machine learning techniques, in particular convolutional neural networks, have been investigated as a method to replace or complement traditional matched fil…