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Cited article:

Euclid preparation

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https://doi.org/10.1016/j.dark.2025.101965

Euclid preparation

G. Rácz, M.-A. Breton, B. Fiorini, A. M. C. Le Brun, H.-A. Winther, Z. Sakr, L. Pizzuti, A. Ragagnin, T. Gayoux, E. Altamura, E. Carella, K. Pardede, G. Verza, K. Koyama, M. Baldi, A. Pourtsidou, F. Vernizzi, A. G. Adame, J. Adamek, S. Avila, C. Carbone, G. Despali, C. Giocoli, C. Hernández-Aguayo, F. Hassani, et al.
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https://doi.org/10.1051/0004-6361/202452185

Quasi-local masses and cosmological coupling of black holes and mimickers

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Journal of Cosmology and Astroparticle Physics 2024 (03) 026 (2024)
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Machine learning unveils the linear matter power spectrum of modified gravity

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Physical Review D 109 (6) (2024)
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Tracking the validity of the quasi-static and sub-horizon approximations in modified gravity

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Journal of Cosmology and Astroparticle Physics 2023 (08) 019 (2023)
https://doi.org/10.1088/1475-7516/2023/08/019

Joint reconstructions of growth and expansion histories from stage-IV surveys with minimal assumptions: Dark energy beyond Λ

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Physical Review D 106 (8) (2022)
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Machine learning constraints on deviations from general relativity from the large scale structure of the Universe

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Physical Review D 106 (10) (2022)
https://doi.org/10.1103/PhysRevD.106.103519