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    • Improved methodology for the automated classification of periodic variable stars 

      Blomme, J.; Sarro, L. M.; O’Donovan, F. T.; Debosscher, J.; Brown, T.; Lopez, M.; Dubath, P.; Rimoldini, L.; Charbonneau, D.; Dunham, E.; Mandushev, G.; Ciardi, D. R.; De Ridder, J.; Aerts, C. (Oxford University Press, 2011)
      We present a novel automated methodology to detect and classify periodic variable stars in a large data base of photometric time series. The methods are based on multivariate Bayesian statistics and use a multistage approach. ...