Neural network classification with CRPS optimization produces calibrated photometric redshift PDFs for DESI Legacy and Pan-STARRS data, achieving σ_NMAD of 0.0153 on LSDR10 and outperforming regression methods.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Random Forest model classifies K2 stars into four categories with over 80% accuracy using effective temperature, luminosity, and FliPer features.
citing papers explorer
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Photometric Redshift PDFs via Neural Network Classification for DESI Legacy Imaging Surveys and Pan-STARRS
Neural network classification with CRPS optimization produces calibrated photometric redshift PDFs for DESI Legacy and Pan-STARRS data, achieving σ_NMAD of 0.0153 on LSDR10 and outperforming regression methods.
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Automatic classification of K2 pulsating stars using machine learning techniques
Random Forest model classifies K2 stars into four categories with over 80% accuracy using effective temperature, luminosity, and FliPer features.