DUNE enables exact data-consistency gradients via VJP when deep unrolled networks operate in representation space, yielding better MRI reconstructions than prior heuristic-DC variants.
Wilcox, Caroline Holmes, and Bruce W
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Identifiability limits in ultrasonic microstructure characterization are governed by forward-map structure and intrinsic stochastic variability, with combined observables improving conditioning through complementary sensitivities.
citing papers explorer
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Deep Unrolled Networks in Representation Space Applied to MRI Reconstruction
DUNE enables exact data-consistency gradients via VJP when deep unrolled networks operate in representation space, yielding better MRI reconstructions than prior heuristic-DC variants.
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Identifiability Limits in Ultrasonic Microstructure Characterisation: A Canonical and Stochastic Framework
Identifiability limits in ultrasonic microstructure characterization are governed by forward-map structure and intrinsic stochastic variability, with combined observables improving conditioning through complementary sensitivities.