Architecture, implementation and parallelization of the software to search for periodic gravitational wave signals. - Gevorg Poghosyan; Sanchit Matta; Achim Streit; Michal Bejger; Andrzej Królak (Comput. Phys. Commun., 2015)

Convolutional neural network classifier for the output of the time-domain $ mathcal{F}$-statistic all-sky search for continuous gravitational waves. - Filip Morawski; Michal Bejger; Pawel Ciecielag (Mach. Learn. Sci. Technol., 2020)

The effect of floating-point precision on narrow-band all-sky continuous gravitational-wave search algorithm. - M. F. Nagy-Egri; Michal Bejger (Astron. Comput., 2021)

Enhancing gravitational-wave science with machine learning. - Elena Cuoco; Jade Powell; Marco Cavaglià; Kendall Ackley; Michal Bejger; Chayan Chatterjee; Michael Coughlin; Scott Coughlin; Paul Easter; Reed Essick; Hunter Gabbard; Timothy Gebhard; et al. (Mach. Learn. Sci. Technol., 2021)

Anomaly detection in gravitational waves data using convolutional autoencoders. - Filip Morawski; Michal Bejger; Elena Cuoco; Luigia Petre (Mach. Learn. Sci. Technol., 2021)

Denoising gravitational-wave signals from binary black holes with a dilated convolutional autoencoder. - Philippe Bacon; Agata Trovato; Michal Bejger (Mach. Learn. Sci. Technol., 2023)