318 citations · 1.1k across the 11 of their papers we have counts for
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astro-ph.IM2016
Of Genes and Machines: application of a combination of machine learning tools to astronomy datasets
S. Heinis, S. Kumar, S. Gezari +8
We apply a combination of a Genetic Algorithms (GA) and Support Vector Machines (SVM) machine learning algorithm to solve two important problems faced by the astronomical community…
astro-ph.IM2015★ 73 cited
Machine learning for transient discovery in Pan-STARRS1 difference imaging
D. E. Wright, S. J. Smartt, K. W. Smith +15
Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many fal…