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Gammaldi, V., Zaldivar, B., Sanchez-Conde, M. A., & Coronado-Blazquez, J. (2023). A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning. Mon. Not. Roy. Astron. Soc., 520(1), 1348–1361.
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de los Rios, M., Petac, M., Zaldivar, B., Bonaventura, N. R., Calore, F., & Iocco, F. (2023). Determining the dark matter distribution in simulated galaxies with deep learning. Mon. Not. Roy. Astron. Soc., 525(4), 6015–6035.
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Curtin, D. et al, & Hirsch, M. (2019). Long-lived particles at the energy frontier: the MATHUSLA physics case. Rep. Prog. Phys., 82(11), 116201–133pp.
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Borsato, M. et al, Zurita, J., Henry, L., Jashal, B. K., & Oyanguren, A. (2022). Unleashing the full power of LHCb to probe stealth new physics. Rep. Prog. Phys., 85(2), 024201–45pp.
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Martin Lozano, V., Sanda Seoane, R. M., & Zurita, J. (2023). Z'-explorer 2.0: Reconnoitering the dark matter landscape. Comput. Phys. Commun., 288, 108729–14pp.
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Ho, S. et al, de Putter, R., & Mena, O. (2012). Clustering of Sloan Digital Sky Survey III Photometric Luminous Galaxies: The Measurement, Systematics and Cosmological Implications. Astrophys. J., 761(1), 14–24pp.
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Cermeño, M., Perez-Garcia, M. A., & Lineros, R. A. (2018). Enhanced neutrino emissivities in pseudoscalar-mediated dark matter annihilation in neutron stars. Astrophys. J., 863(2), 157–9pp.
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Villanueva-Domingo, P., & Villaescusa-Navarro, F. (2021). Removing Astrophysics in 21 cm Maps with Neural Networks. Astrophys. J., 907(1), 44–14pp.
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Villanueva-Domingo, P., & Ichiki, K. (2023). 21 cm forest constraints on primordial black holes. Publ. Astron. Soc. Jpn., 75(SP1), S33–S49.
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Ahyoune, S. et al, Gimeno, B., & Reina-Valero, J. (2023). A Proposal for a Low-Frequency Axion Search in the 1-2 μeV Range and Below with the BabyIAXO Magnet. Ann. Phys., 535(12), 2300326–23pp.
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