Peer-reviewed work
Papers on field-level cosmological inference, the halo–galaxy connection, and interpretable machine learning. You can also find my articles on my Google Scholar profile.
Published in ApJ
One equation from one galaxy can predict cosmology
Liao, K., Villaescusa-Navarro, F., Teyssier, R., et al. 2026, ApJ. doi:10.3847/1538-4357/ae64e3 https://iopscience.iop.org/article/10.3847/1538-4357/ae64e3
Published in A&A
Environmental and NF are what we need for galaxy bias
Riveros-Jara, C., Montero-Dorta, A. D., Rodrigues, N. V. N., et al. 2026, AAP, doi:10.1051/0004-6361/202659262 https://www.aanda.org/articles/aa/full_html/2026/07/aa59262-26/aa59262-26.html
Published in ApJ
SAMs are just what we need for field-level cosmology?
Natalí S. M. de Santi, Francisco Villaescusa-Navarro, Pablo Araya-Araya, et al. 2026, ApJ. doi:10.3847/1538-4357/ae84b4 https://iopscience.iop.org/article/10.3847/1538-4357/ae84b4
Published in A&A
Normalizing flows, Gaussian Likelihood and regression to classification solving halo-galaxy scatter problem
Rodrigues, N. V. N., de Santi, N. S. M., Abramo, R., et al. 2025, AAP. doi:10.1051/0004-6361/202453284 https://www.aanda.org/articles/aa/full_html/2025/06/aa53284-24/aa53284-24.html
Published in JCAP
GNNs can deal with observational effects
de Santi, N. S. M., Villaescusa-Navarro, F., Raul Abramo, L., et al. 2025, JCAP. doi:10.1088/1475-7516/2025/01/082 https://iopscience.iop.org/article/10.1088/1475-7516/2025/01/082
Published in ApJ
Why does Astrid is so good for getting robust models?
Ni, Y., Genel, S., Anglés-Alcázar, D., et al. 2023, ApJ, 959, 2, 136. doi:10.3847/1538-4357/ad022a https://iopscience.iop.org/article/10.3847/1538-4357/ad022a
Published in ApJ
Using symbolic regression to understand GNNs
Shao, H., de Santi, N. S. M., Villaescusa-Navarro, F., et al. 2023, ApJ, 956, 2, 149. doi:10.3847/1538-4357/acee6f https://iopscience.iop.org/article/10.3847/1538-4357/acee6f
Published in RASAB2023
Image denoising for a robust model
de Santi, N. S. M. and Abramo, L. R. 2023 https://sab-astro.org.br/wp-content/uploads/2023/04/NataliSolerMatubarodeSanti.pdf
Published in arXiv
NF for mapping the halo-galaxy connection using cosmological parameters and CAMELS
Lovell, C. C., Hassan, S., Anglés-Alcázar, D., et al. 2023, arXiv:2307.06967. doi:10.48550/arXiv.2307.06967 [https://arxiv.org/abs/2307.06967](https://arxiv.org/abs/2307.06967)
Published in MNRAS
Regression to classification solving halo-galaxy scatter problem
Natália V N Rodrigues, Natalí S M de Santi, et al., 2023, https://doi.org/10.1093/mnras/stad1186 https://doi.org/10.1093/mnras/stad1186
Published in ApJ
First ML robust method to predict $\Omega_{m}$
Natalí S. M. de Santi et al 2023 ApJ 952 69 https://iopscience.iop.org/article/10.3847/1538-4357/acd1e2/meta
Published in Blucher Physics Proceedings
First steps to improve cosmological covariance matrices
de Santi, N. S. M. and Abramo, L. R. 2022, DOI: 10.5151/astrocientistas2021-11 https://www.proceedings.blucher.com.br/article-details/primeiros-passos-na-obteno-de-parmetros-cosmolgicos-utilizando-matrizes-de-covarincia-cosmolgicas-sem-rudo-37453
Published in JCAP
Image denoising for a robust model
de Santi, N. S. M. and Abramo, L. R. 2022, DOI:10.1088/1475-7516/2022/09/013 https://iopscience.iop.org/article/10.1088/1475-7516/2022/09/013
Published in MNRAS
First approach: stacked methods and SMOGN
Natalí S. M. de Santi, et al. 2022, https://doi.org/10.1093/mnras/stac1469 https://doi.org/10.1093/mnras/stac1469
Published in Springer
First steps to the halo-galaxy connection
de Santi, N. S. M. and et al., 2023 https://link.springer.com/book/10.1007/978-3-031-34167-0
Published in Brazilian Journal of Physics
This paper contains the numerical results from my Masters.
de Santi, N.S.M., Santarelli, R., 2019. https://doi.org/10.1007/s13538-019-00708-y https://link.springer.com/article/10.1007%2Fs13538-019-00708-y
Published in Revista Brasileira de Ensino de Física
This paper comprehends a first part of my Masters.
Santi, Natali Soler Matubaro de, & Santarelli, Raphael. 2019. https://doi.org/10.1590/1806-9126-rbef-2018-0312 http://www.scielo.br/pdf/rbef/v41n3/1806-9126-RBEF-41-3-e20180312.pdf