Spectral Uncertainty Decomposition for Sparse Bayesian Learning
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...