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  • Classifying galaxies according to their H I content 

    Andrianomena, Sambatra; Rafieferantsoa, Mika; Dave, Romeel (Oxford University Press, 2020)
    We use machine learning to classify galaxies according to their H I content, based on both their optical photometry and environmental properties. The data used for our analyses are the outputs in the range z = 0–1 from ...
  • Predicting the neutral hydrogen content of galaxies from optical data using machine learning 

    Rafieferantsoa, Mika; Andrianomena, Sambatra; Dave, Romeel (Oxford University Press, 2018)
    We develop a machine learning-based framework to predict the Hi content of galaxies using more straightforwardly observable quantities such as optical photometry and environmental parameters. We train the algorithm on z ...