4 citations · 8 across the 5 of their papers we have counts for
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astro-ph.GA2025★ 1 cited
Optimized HDBSCAN clustering for reconstructing the merger history of the Milky Way: applications and limitations
Andrea Sante, Andreea S. Font, Dharmesh Mistry +2
Clustering algorithms can help reconstruct the assembly history of the Milky Way by identifying groups of stars sharing similar properties in a kinematical or chemical abundance sp…
astro-ph.GA2024★ 4 cited
Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?
Andrea Sante, Andreea S. Font, Sandra Ortega-Martorell +2
We present several machine learning (ML) models developed to efficiently separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later a…