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pro vyhledávání: '"Golini A"'
Random Forest (RF) is a widely used machine learning algorithm known for its flexibility, user-friendliness, and high predictive performance across various domains. However, it is non-interpretable. This can limit its usefulness in applied sciences,
Externí odkaz:
http://arxiv.org/abs/2408.05537
Autor:
Zaritsky, Dennis, Golini, Giulia, Donnerstein, Richard, Trujillo, Ignacio, Akhlaghi, Mohammad, Chamba, Nushkia, D'Onofrio, Mauro, Eskandarlou, Sepideh, Hosseini-ShahiSavandi, S. Zahra, Infante-Sainz, Raúl, Martin, Garreth, Montes, Mireia, Román, Javier, Sedighi, Nafise, Sharbaf, Zahra
We present an overview of the LIGHTS (LBT Imaging of Galactic Halos and Tidal Structures) survey, which currently includes 25 nearby galaxies that are on average $\sim$ 1 mag fainter than the Milky Way, and a catalog of 54 low central surface brightn
Externí odkaz:
http://arxiv.org/abs/2406.01912
Publikováno v:
A&A 689, A344 (2024)
AGC 114905 is a dwarf gas-rich ultra-diffuse galaxy seemingly in tension with the cold dark matter (CDM) model. Specifically, the galaxy appears to have an extremely low-density halo and a high baryon fraction, while CDM predicts dwarfs to have very
Externí odkaz:
http://arxiv.org/abs/2404.06537
Publikováno v:
A&A, 684, A99 (2024)
A number of scenarios have been proposed to explain the low velocity dispersion (and hence possible absence of dark matter) of the low surface brightness galaxies NGC1052-DF2 and NGC1052-DF4. Most of the proposed mechanisms are based on the removal o
Externí odkaz:
http://arxiv.org/abs/2402.04304
Autor:
Eskandarlou, Sepideh, Akhlaghi, Mohammad, Infante-Sainz, Raúl, Saremi, Elham, Raji, Samane, Sharbaf, Zahra, Golini, Giulia, Ghaffari, Zohreh, Knapen, Johan H.
Calibration of pixel values is a fundamental step for accurate measurements in astronomical imaging. In astronomical jargon this is known as estimating zero point magnitude. Here, we introduce a newly added script in GNU Astronomy Utilities (Gnuastro
Externí odkaz:
http://arxiv.org/abs/2312.04263
Autor:
Montes, Mireia, Trujillo, Ignacio, Karunakaran, Ananthan, Infante-Sainz, Raul, Spekkens, Kristine, Golini, Giulia, Beasley, Michael, Cebrian, Maria, Chamba, Nushkia, D'Onofrio, Mauro, Kelvin, Lee, Roman, Javier
Publikováno v:
A&A 681, A15 (2024)
Almost Dark Galaxies are objects that have eluded detection by traditional surveys such as the Sloan Digital Sky Survey (SDSS). The low surface brightness of these galaxies ($\mu_r$(0)$>26$ mag/arcsec^2), and hence their low surface stellar mass dens
Externí odkaz:
http://arxiv.org/abs/2310.12231
Publikováno v:
Environmetrics, 2024, e2865
Spatial mapping of biodiversity is crucial to investigate spatial variations in natural communities. Several indices have been proposed in the literature to represent biodiversity as a single statistic. However, these indices only provide information
Externí odkaz:
http://arxiv.org/abs/2309.14948
Autor:
Otto, Philipp, Moro, Alessandro Fusta, Rodeschini, Jacopo, Shaboviq, Qendrim, Ignaccolo, Rosaria, Golini, Natalia, Cameletti, Michela, Maranzano, Paolo, Finazzi, Francesco, Fassò, Alessandro
This study presents a comparative analysis of three predictive models with an increasing degree of flexibility: hidden dynamic geostatistical models (HDGM), generalised additive mixed models (GAMM), and the random forest spatiotemporal kriging models
Externí odkaz:
http://arxiv.org/abs/2309.07285
Autor:
Román, Javier, Rich, R. Michael, Ahvazi, Niusha, Sales, Laura, Li, Chester, Golini, Giulia, Trujillo, Ignacio, Knapen, Johan H., Peletier, Reynier F., Sánchez-Alarcón, Pablo M.
Publikováno v:
A&A 679, A157 (2023)
The study of dynamically cold stellar streams reveals information about the gravitational potential where they reside and provides important constraints on dark matter properties. However, their intrinsic faintness makes detection beyond Local enviro
Externí odkaz:
http://arxiv.org/abs/2305.03073
Random Forest (RF) is a well-known data-driven algorithm applied in several fields thanks to its flexibility in modeling the relationship between the response variable and the predictors, also in case of strong non-linearities. In environmental appli
Externí odkaz:
http://arxiv.org/abs/2303.04693