Now showing items 1-2 of 2

    • 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 ...