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Dimensionality Reduction of SDSS Spectra with Variational Autoencoders

  • Authors: Stephen K. N. Portillo, John K. Parejko, Jorge R. Vergara, and Andrew J. Connolly

2020 The Astronomical Journal 160 45.

  • Provider: AAS Journals

Caption: Figure 17.

Variance (left) and bias (right) of the latent mean of each latent parameter (one line per parameter) when white noise is added to a high-S/N spectrum, in units of the latent variance. The latent variance underestimates the uncertainty in latent space for spectra with S/N < 25, which are 90% of the spectra. The latent mean is not significantly biased if the spectrum has S/N ⪆ 8.

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