PITA, a new semi-supervised deep learning algorithm, outperforms prior photo-z methods by using a triple-task loss on images, colors, and available redshifts to produce a smooth latent space.
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Observational analysis of 86 z~1 galaxies shows winds correlate with galaxy-wide SFR and Σ_SFR, not compact regions, implying distributed star formation drives outflows.
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Optimizing Deep Learning Photometric Redshifts for the Roman Space Telescope with HST/CANDELS
PITA, a new semi-supervised deep learning algorithm, outperforms prior photo-z methods by using a triple-task loss on images, colors, and available redshifts to produce a smooth latent space.
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The Importance of Galaxy-Wide Star Formation in Driving Winds at z~1
Observational analysis of 86 z~1 galaxies shows winds correlate with galaxy-wide SFR and Σ_SFR, not compact regions, implying distributed star formation drives outflows.