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Found 2 papers, 1 papers with code
Estimating Galactic Distances From Images Using Self-supervised Representation Learning
We use a contrastive self-supervised learning framework to estimate distances to galaxies from their photometric images.
Self-Supervised Representation Learning for Astronomical Images
We show that, without the need for labels, self-supervised learning recovers representations of sky survey images that are semantically useful for a variety of scientific tasks.
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