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Inverse theory can never be wrong because it's just theory.
Where problems arise and opportunities are overlooked
is where practitioners grab and use inverse theory
without recognizing that alternate assumptions might be better.
Here I formulate
to supplement (or replace) familiar regularizations in image estimation.
Applications appear abundant.