162 citations · 162 across the 2 of their papers we have counts for
3 papers
From Photometric Redshifts to Improved Weather Forecasts: machine learning and proper scoring rules as a basis for interdisciplinary work
Kai Lars Polsterer, Antonio D'Isanto, Sebastian Lerch
The amount, size, and complexity of astronomical data-sets and databases are growing rapidly in the last decades, due to new technologies and dedicated survey telescopes. Besides d…
Return of the features. Efficient feature selection and interpretation for photometric redshifts
Antonio D'Isanto, Stefano Cavuoti, Fabian Gieseke +1
The explosion of data in recent years has generated an increasing need for new analysis techniques in order to extract knowledge from massive datasets. Machine learning has proved…
Photometric redshift estimation via deep learning
Antonio D'Isanto, Kai Lars Polsterer
The need to analyze the available large synoptic multi-band surveys drives the development of new data-analysis methods. Photometric redshift estimation is one field of application…