Ages inferred for red giant stars via machine learning are generally insensitive to hyperparameters and architecture but somewhat sensitive to training set choice, especially for the oldest, coolest, and lowest-metallicity stars.
N., Guhathakurta, P., Zhang, A
2 Pith papers cite this work. Polarity classification is still indexing.
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The PFS Galactic Archaeology survey will observe thousands of stars in Local Group systems to measure density profiles in dwarfs and compare assembly histories of M31 and the Milky Way.
citing papers explorer
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Evaluating the Sensitivity of the Age Inferences of Red Giant Stars to Machine Learning Methodology
Ages inferred for red giant stars via machine learning are generally insensitive to hyperparameters and architecture but somewhat sensitive to training set choice, especially for the oldest, coolest, and lowest-metallicity stars.
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Galactic Archaeology with the Subaru `\=Onohi`ula Prime Focus Spectrograph Strategic Program
The PFS Galactic Archaeology survey will observe thousands of stars in Local Group systems to measure density profiles in dwarfs and compare assembly histories of M31 and the Milky Way.