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S Voskresenskaia, A Meshcheryakov and N Lyskova Monthly Notices of the Royal Astronomical Society 531(1) 1998 (2024) https://doi.org/10.1093/mnras/stae1269
Self-supervised component separation for the extragalactic submillimetre sky
Impact of astrophysical effects on the dark matter mass constraint with 21 cm intensity mapping
Koya Murakami, Atsushi J Nishizawa, Kentaro Nagamine and Ikko Shimizu Monthly Notices of the Royal Astronomical Society 530(2) 2052 (2024) https://doi.org/10.1093/mnras/stae945
YOLO–CL: Galaxy cluster detection in the SDSS with deep machine learning
Statistical Study of Central Radio Sources in Regions with the Sunyaev–Zeldovich Effect
D. I. Solovyov, O. V. Verkhodanov, O. S. Ulakhovich, N. V. Verkhodanova and M. L. Khabibullina Astronomy Reports 66(6) 441 (2022) https://doi.org/10.1134/S106377292207006X
An Extended Catalog of Sunyaev–Zeldovich Objects from Planck Data with Deep Learning
What to expect from dynamical modelling of cluster haloes – II. Investigating dynamical state indicators with Random Forest
Qingyang Li, Jiaxin Han, Wenting Wang, et al. Monthly Notices of the Royal Astronomical Society 514(4) 5890 (2022) https://doi.org/10.1093/mnras/stac1739
DeepSZ: identification of Sunyaev–Zel’dovich galaxy clusters using deep learning
Search for Galaxy Cluster Candidates in the Cosmic Microwave Background Maps of the Planck Space Mission Using a Convolutional Neural Network Based on the Method of Tracing the Sunyaev–Zeldovich Effect
O. V. Verkhodanov, A. P. Topchieva, A. D. Oronovskaya, S. A. Bazrov and D. A. Shorin Astrophysical Bulletin 76(2) 123 (2021) https://doi.org/10.1134/S1990341321020103
Constraining cosmology with a new all-sky Compton parameter map from the Planck PR4 data
Hideki Tanimura, Marian Douspis, Nabila Aghanim and Laura Salvati Monthly Notices of the Royal Astronomical Society 509(1) 300 (2021) https://doi.org/10.1093/mnras/stab2956