![Analysis of the stellar parameters derived with our methodology. The dots are colour-coded according to the estimated metallicity. The size of the dots is proportional to the estimated projected rotational velocity. The top left panel shows a Kiel diagram, with the red, black, and blue dashed lines corresponding to 5 Gyr PARSEC isochrones with [M/H] = −0.4, 0.0 and 0.1 dex, respectively. Empty squares represent the stars reported to have a behaviour akin to subdwarfs both in Mar21 and Schw19 (same for bottom left panel). Top right: black and grey dashed lines correspond to solar metallicity PARSEC isochrones for 5 and 0.1 Gyr, respectively. Black and grey dotted lines correspond to solar metallicity Baraffe et al. (2015) isochrones for 5 and 0.1 Gyr, respectively. Bottom left: triangles represent stars identified as Hα active in Schöfer et al. (2019). Empty stars depict members of the thick disc Galactic population (Cortés-Contreras et al., in prep.). Bottom right: plus symbols correspond to stars identified as members of the young disc Galactic population by Cortés-Contreras et al. (in prep.). Empty circles represent stars with a possible membership in a young stellar associaton, as explained in Section 4.1. -- astro-ph.SR](https://i0.wp.com/astrobiology.com/wp-content/uploads/2024/05/Using-Autoencoders-And-Deep.png?resize=1200%2C717&ssl=1)
Deep learning (DL) techniques are a promising approach among the set of methods used in the ever-challenging determination of stellar parameters in M dwarfs.
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Tricorder Tech: An AI-Powered Hand Held Medical Device
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Posted inAI - Data - Apps - Cybernetics, Atmospheres, Climate, Weather, Brown Dwarfs, Exoplanets, -moons, -comets, Imaging & Spectroscopy, Status Report
FlopPITy: Enabling Self-consistent Exoplanet Atmospheric Retrievals With Machine Learning
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