A CNN with attention and shared latent space recovers SFHs and metallicities from spectro-photometric data with ~0.12 dex age and ~0.03 dex metallicity dispersion while running thousands of times faster than full spectral fitting.
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astro-ph.GA 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
The analysis identifies ~300 pc and ~200 pc transition scales in PAH emission and ISM density PDFs in nearby galaxies by decomposing JWST mid-IR images into compact and diffuse components.
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Determining star formation histories and age-metallicity relations with convolutional neural networks
A CNN with attention and shared latent space recovers SFHs and metallicities from spectro-photometric data with ~0.12 dex age and ~0.03 dex metallicity dispersion while running thousands of times faster than full spectral fitting.
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Uncovering the multi-scale structure of dust distribution in nearby galaxies
The analysis identifies ~300 pc and ~200 pc transition scales in PAH emission and ISM density PDFs in nearby galaxies by decomposing JWST mid-IR images into compact and diffuse components.