A generative latent diffusion framework jointly infers photometric-redshift PDFs and reconstructs rest-frame spectra from photometric data after pre-training a spectral autoencoder on millions of spectra.
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astro-ph.GA 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A multimodal neural network trained on MPA-JHU references produces SFR, stellar mass, and metallicity estimates for 547 million low-redshift galaxies in DESI LS DR10.
citing papers explorer
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Joint probabilistic inference of galaxy redshifts and rest-frame spectra from photometric fluxes with latent diffusion
A generative latent diffusion framework jointly infers photometric-redshift PDFs and reconstructs rest-frame spectra from photometric data after pre-training a spectral autoencoder on millions of spectra.
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A Value-added Physical Properties Catalog for Low-redshift Galaxies from DESI Legacy Imaging Surveys DR10
A multimodal neural network trained on MPA-JHU references produces SFR, stellar mass, and metallicity estimates for 547 million low-redshift galaxies in DESI LS DR10.