Zobrazeno 1 - 10
of 394
pro vyhledávání: '"Magris, P."'
Autor:
Cuevas-Otahola, Bolivia, Mateu, Cecilia, Cabrera-Ziri, Ivan, Bruzual, Gustavo, Hernández-Pérez, Fabiola, Magris, Gladis, Baumgardt, Holger
Recent works have challenged our canonical view of RR Lyrae (RRL) stars as tracers of exclusively old populations ($\gtrsim10$~Gyr) by proposing a fraction of these stars to be of intermediate ages ($\sim$2-5~Gyr). Since it is currently not possible
Externí odkaz:
http://arxiv.org/abs/2411.12741
Autor:
Micolta, Marbely, Calvet, Nuria, Thanathibodee, Thanawuth, C., Gladis Magris, Manara, Carlo F., Venuti, Laura, Alcalá, Juan Manuel, Herczeg, Gregory J.
We present a study of the abundance of calcium in the innermost disk of 70 T Tauri stars in the star-forming regions of Chamaeleon I, Lupus and Orion OB1b. We use calcium as a proxy for the refractory material that reaches the inner disk. We used mag
Externí odkaz:
http://arxiv.org/abs/2410.17327
Publikováno v:
A&A 690, A199 (2024)
This work aims to analyze some of the polluters proposed in the self-enrichment scenarios put forward to explain the multiple populations in globular clusters (GCs), extending previous studies. Three scenarios with different polluter stars were teste
Externí odkaz:
http://arxiv.org/abs/2408.09001
Autor:
Prieto, Almudena, C., Gladis Magris, Bruzual, Gustavo, Fernández-Ontiveros, Juan A., Burkert, Andreas
Understanding star formation in galaxies requires resolving the physical scale on which star formation often occurs: the scale of star clusters. We present a multiwavelength, eight-parsec resolution study of star formation in the circumnuclear star c
Externí odkaz:
http://arxiv.org/abs/2407.20860
Publikováno v:
IEEE Journal of Biomedical and Health Informatics, 2024
Variational Inference (VI) is a commonly used technique for approximate Bayesian inference and uncertainty estimation in deep learning models, yet it comes at a computational cost, as it doubles the number of trainable parameters to represent uncerta
Externí odkaz:
http://arxiv.org/abs/2404.06421
Autor:
Magris, Martin, Iosifidis, Alexandros
The Bayesian estimation of GARCH-family models has been typically addressed through Monte Carlo sampling. Variational Inference is gaining popularity and attention as a robust approach for Bayesian inference in complex machine learning models; howeve
Externí odkaz:
http://arxiv.org/abs/2310.03435
Autor:
Luka Marinov, Gabriele Magris, Gabriele Di Gaspero, Michele Morgante, Edi Maletić, Marijan Bubola, Ivan Pejić, Goran Zdunić
Publikováno v:
BMC Plant Biology, Vol 24, Iss 1, Pp 1-16 (2024)
Abstract Background Croatia is a geographically small country with a remarkable diversity of cultivated and spontaneous grapevines. Local germplasm has been characterised by microsatellite markers, but a detailed analysis based on single nucleotide p
Externí odkaz:
https://doaj.org/article/c9dd2509e606428296c5774f6f4014c0
Autor:
Micolta, Marbely, Calvet, Nuria, Thanathibodee, Thanawuth, C., Gladis Magris, Colmenares, María José, Díaz, Jesús V., Alzate-Trujillo, Jairo
We present a study of the Ca II K and IR-triplet lines in a sample of Classical T Tauri stars in the Chamaeleon I star-forming region. We study X-shooter spectra of the stars in the sample and find that in some of these stars the Ca II lines are much
Externí odkaz:
http://arxiv.org/abs/2306.10643
Autor:
Alzate, Jairo A., Bruzual, Gustavo, Kounkel, Marina, Magris, Gladis, Hartmann, Lee, Calvet, Nuria, Cao, Lyra
We develop statistical methods within a Bayesian framework to infer the star formation history from photometric surveys of pre-main sequence populations. Our procedures include correcting for biases due to extinction in magnitude-limited surveys, and
Externí odkaz:
http://arxiv.org/abs/2305.11823
Autor:
Magris, Martin, Iosifidis, Alexandros
The last decade witnessed a growing interest in Bayesian learning. Yet, the technicality of the topic and the multitude of ingredients involved therein, besides the complexity of turning theory into practical implementations, limit the use of the Bay
Externí odkaz:
http://arxiv.org/abs/2211.11865