723 citations · 5.7k across the 104 of their papers we have counts for
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astro-ph.IM2020★ 18 cited
Machines Learn to Infer Stellar Parameters Just by Looking at a Large Number of Spectra
Nima Sedaghat, Martino Romaniello, Jonathan E. Carrick +1
Machine learning has been widely applied to clearly defined problems of astronomy and astrophysics. However, deep learning and its conceptual differences to classical machine learn…
astro-ph.SR2020★ 2 cited
Towards precise and accurate Cepheid chemical abundances for 1 $\mbox{H}_0$ measurement: temperature determination
Sara Mancino, Martino Romaniello, Richard I. Anderson +1
One of the outstanding problems in modern physics is the origin is of accelerated expansion of the universe. High-precision determinations of the Hubble parameter $\mbox{H}_0$ at d…