A variational autoencoder learns to generate and reconstruct quasar spectra from SDSS data, reproducing median and variance properties while enabling photometry synthesis and absorption-line interpolation without ad-hoc tuning.
2024a, A deep learning model for the density profiles of subhaloes in IllustrisTNG, arXiv:2403.12125 [astro- ph]
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QUEST (Quasar Unsupervised Encoder and Synthesis Tool): A machine learning framework to generate quasar spectra
A variational autoencoder learns to generate and reconstruct quasar spectra from SDSS data, reproducing median and variance properties while enabling photometry synthesis and absorption-line interpolation without ad-hoc tuning.