Improving machine learning-derived photometric redshifts and physical property estimates using unlabelled observations
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DOI: 10.1093/mnras/stac3596
Abstract: In the era of huge astronomical surveys, machine learning offers promising solutions for the efficient estimation of galaxy properties. The traditional, ‘supervised’ paradigm for the application of machine learning involves training a model on labelled… read more here.
Keywords: photometric redshifts; machine; machine learning; derived photometric ... See more keywords