Automatic Survey-invariant Classification of Variable Stars

@article{Benavente2017AutomaticSC,
  title={Automatic Survey-invariant Classification of Variable Stars},
  author={Patricio Benavente and Pavlos Protopapas and Karim Pichara},
  journal={The Astrophysical Journal},
  year={2017},
  volume={845}
}
Machine learning techniques have been successfully used to classify variable stars on widely studied astronomical surveys. These data sets have been available to astronomers long enough, thus allowing them to perform deep analysis over several variable sources and generating useful catalogs with identified variable stars. The products of these studies are labeled data that enable supervised learning models to be trained successfully. However, when these models are blindly applied to data from… 
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