21 citations · 32 across the 7 of their papers we have counts for
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cs.LG2023★ 3 cited
Rician likelihood loss for quantitative MRI using self-supervised deep learning
Christopher S. Parker, Anna Schroder, Sean C. Epstein +3
Purpose: Previous quantitative MR imaging studies using self-supervised deep learning have reported biased parameter estimates at low SNR. Such systematic errors arise from the cho…
cs.CV2023★ 3 cited
Interpretable Alzheimer's Disease Classification Via a Contrastive Diffusion Autoencoder
Ayodeji Ijishakin, Ahmed Abdulaal, Adamos Hadjivasiliou +2
In visual object classification, humans often justify their choices by comparing objects to prototypical examples within that class. We may therefore increase the interpretability…