most citedExploring X-ray variability with unsupervised machine learning I. Self-organizing maps applied to XMM-Newton data

15 citations · 15 across the 1 of their papers we have counts for

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astro-ph.IM2022★ 15 cited

Exploring X-ray variability with unsupervised machine learning I. Self-organizing maps applied to XMM-Newton data

Miloš Kovačević, Mario Pasquato, Martino Marelli +3

XMM-Newton provides unprecedented insight into the X-ray Universe, recording variability information for hundreds of thousands of sources. Manually searching for interesting patter…