Deep learning classification in asteroseismology using an improved neural network: results on 15 000 Kepler red giants and applications to K2 and TESS data-Reference-Cited by-同舟云学术

Deep learning classification in asteroseismology using an improved neural network: results on 15 000 Kepler red giants and applications to K2 and TESS data

Published:2018-02-22 Issue:3 Volume:476 Page:3233-3244
ISSN:0035-8711
Container-title:Monthly Notices of the Royal Astronomical Society
language:en
Short-container-title:

Author:

Hon Marc¹^ORCID,Stello Dennis¹²³,Yu Jie²

Affiliation:

1. School of Physics, The University of New South Wales, Sydney NSW 2052, Australia

2. Sydney Institute for Astronomy (SIfA), School of Physics, University of Sydney, NSW 2006, Australia

3. Stellar Astrophysics Centre, Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, DK-8000 Aarhus C, Denmark

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

Link

http://academic.oup.com/mnras/article-pdf/476/3/3233/24458285/sty483.pdf

Reference44 articles.

1. Gravity modes as a way to distinguish between hydrogen- and helium-burning red giant stars

2. Kepler Planet-Detection Mission: Introduction and First Results

3. VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY

4. THE ASTEROSEISMIC POTENTIAL OFTESS: EXOPLANET-HOST STARS

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