The journals General Relativity and Gravitation and Living Reviews in Relativity have opened a joined Topical Collection on “Machine Learning in Gravitational-Wave Science”, which aims to include review articles and original research.
While the recent Living Review “Applications of machine learning in gravitational-wave research with current interferometric detectors” by Cuoco et al. (2025) serves as a general introduction to the topic, we encourage authors to submit their work on specific applications of machine learning methods, neural networks, and deep learning techniques in GW data analysis, including noise reduction and mitigation, signal detection, parameter estimation, classification and interpretation of astrophysical sources to the journal General Relativity and Gravitation.