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Found 2 papers, 2 papers with code
Strong Gravitational Lensing Parameter Estimation with Vision Transformer
Quantifying the parameters and corresponding uncertainties of hundreds of strongly lensed quasar systems holds the key to resolving one of the most important scientific questions: the Hubble constant ($H_{0}$) tension.
Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds
We introduce the state-of-the-art deep learning Denoising Diffusion Probabilistic Model (DDPM) as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps.
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