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Improving Generalization and Uncertainty Quantification of Photometric Redshift Models

  • Authors: Jonathan Soriano, Tuan Do, Srinath Saikrishnan, Vikram Seenivasan, Bernie Boscoe, Jack Singal, Evan Jones

Jonathan Soriano et al 2026 The Astronomical Journal 171 .

  • Provider: AAS Journals

Caption: Figure 2.

Three datasets: a sample of 500,000 galaxies from HSC-PDR2 (H. Aihara et al. 2019), GalaxiesML (T. Do et al. 2024) with spectroscopic redshift ground truth, and TransferZ (this work) with COSMOS2020 catalog (J. R. Weaver et al. 2022) multiband imaging redshift ground truth. The distributions of the dataset in redshift (top), i-band magnitude (middle), and color–color (bottom) show how the datasets complement each other to help the models generalize beyond the range of brightness and color sampled by a spectroscopic survey.

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