14 citations · 29 across the 3 of their papers we have counts for
3 papers
Using autoencoders and deep transfer learning to determine the stellar parameters of 286 CARMENES M dwarfs
P. Mas-Buitrago, A. González-Marcos, E. Solano +9
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. In this context, trans…
The CARMENES search for exoplanets around M dwarfs -- A deep transfer learning method to determine Teff and [M/H] of target stars
A. Bello-García, V. M. Passegger, J. Ordieres-Meré +17
The large amounts of astrophysical data being provided by existing and future instrumentation require efficient and fast analysis tools. Transfer learning is a new technique promis…
J-PLUS: Discovery and characterisation of ultracool dwarfs using Virtual Observatory tools II. Second data release and machine learning methodology
P. Mas-Buitrago, E. Solano, A. González-Marcos +20
Ultracool dwarfs (UCDs) comprise the lowest mass members of the stellar population and brown dwarfs, from M7 V to cooler objects with L, T, and Y spectral types. Most of them have…