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Beyond Sparsity: Weight Location and Network Context in Pruned MRI Reconstruction
Pruning reduces the number of weights in magnetic resonance imaging (MRI) reconstruction networks. Equal sparsity, however, can retain weights with different computational roles and different compatibility with the trained network. We study these effects across 120 convolutional U-Net and vision tra
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