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A spectral framework based on the singular value structure of the prior-preconditioned forward operator is proposed, which provides an exact, interpretable decomposition of the posterior covariance into data-informed and indeterminacy epistemic components, enabling precise accounting of uncertainty reduction through Ba...
Experimental results show that the learned correction variants improve reconstruction performance and convergence behavior over the baseline unfolded solver while preserving its algorithmic transparency.
The results indicate that one-sided H\"older curvature is an effective adaptive step-size signal when full-gradient variation is inflated by directions that do not hinder descent.
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