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Dusty Stellar Source Classification by Implementing Machine Learning Methods Based on Spectroscopic Observations in the Magellanic Clouds
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Investigating episodic mass loss in evolved massive stars
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A Massive Yellow Supergiant in the Far Outer Disk of M31: Evidence for in Situ Massive Star Formation beyond the Optical Radius
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Near-infrared characterization of evolved massive stars in M31 and M33
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Heartbeat Stars Recognition Based on Recurrent Neural Networks: Method and Validation
Min-Yu Li, Sheng-Bang Qian, Li-Ying Zhu, Wen-Ping Liao, Lin-Feng Chang, Er-Gang Zhao, Xiang-Dong Shi, Fu-Xing Li, Qi-Bin Sun and Ping Li The Astronomical Journal 170(3) 161 (2025) https://doi.org/10.3847/1538-3881/aded86
Investigating the metallicity dependence of the mass-loss rate relation of red supergiants
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Investigating episodic mass loss in evolved massive stars
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Applications of machine learning in astrochemistry
The effect of mass loss in models of red supergiants in the Small Magellanic Cloud
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Red Supergiants in the Milky Way and Nearby Galaxies
Investigating episodic mass loss in evolved massive stars
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Discovering New B[e] Supergiants and Candidate Luminous Blue Variables in Nearby Galaxies
Physical Properties of 5000 Cool Large Magellanic Cloud Supergiants with Gaia XP Spectra: A Detailed Portrait of the Upper H-R Diagram Hints at Missing Supernova Progenitors
Data mining techniques on astronomical spectra data – II. Classification analysis
Haifeng Yang, Lichan Zhou, Jianghui Cai, et al. Monthly Notices of the Royal Astronomical Society 518(4) 5904 (2022) https://doi.org/10.1093/mnras/stac3292