1.2k citations · 5.1k across the 72 of their papers we have counts for
4 papers · 1 filter
Tuning target selection algorithms to improve galaxy redshift estimates
Ben Hoyle, Kerstin Paech, Markus Michael Rau +2
We showcase machine learning (ML) inspired target selection algorithms to determine which of all potential targets should be selected first for spectroscopic follow up. Efficient t…
Accurate photometric redshift probability density estimation - method comparison and application
Markus Michael Rau, Stella Seitz, Fabrice Brimioulle +4
We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density fu…
Anomaly detection for machine learning redshifts applied to SDSS galaxies
Ben Hoyle, Markus Michael Rau, Kerstin Paech +3
We present an analysis of anomaly detection for machine learning redshift estimation. Anomaly detection allows the removal of poor training examples, which can adversely influence…
Data augmentation for machine learning redshifts applied to SDSS galaxies
Ben Hoyle, Markus Michael Rau, Christopher Bonnett +2
We present analyses of data augmentation for machine learning redshift estimation. Data augmentation makes a training sample more closely resemble a test sample, if the two base sa…