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Quan-Feng Xu

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Open access Sep 2026

From Observation to Ground Truth: Reconstruction Losses of Galaxy Imaging Under Heteroscedastic Noise

Deep learning is widely used to analyze galaxy images, and the reconstruction loss determines which image features a model prioritizes during training. Mean squared error (MSE) and mean absolute error (MAE) correspond to homoscedastic Gaussian and Laplace likelihoods, respectively, whereas the inverse-variance-weighted...

Ren-Hao Ye, Shi-Yin Shen, Quan-Feng Xu · 0 citations

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