An iterative data-consistent inversion procedure converges to a measure satisfying multiple push-forward constraints, minimizing cumulative f-divergence and yielding the maximum-entropy solution under uniform initialization.
and Leibler, R., On information and sufficiency,The Annals of Mathematical Statistics, 22:79–86
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Iterative Data-Consistent Inversion with Multiple Push-forward Constraints
An iterative data-consistent inversion procedure converges to a measure satisfying multiple push-forward constraints, minimizing cumulative f-divergence and yielding the maximum-entropy solution under uniform initialization.