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Developing learned regularization for geophysical inversions Hewson, Chad

Abstract

Geophysical inverse problems can be posed as the minimization of an objective function where one term (ϕ[sub d]) is a data misfit function and another (ϕ[sub m]) is a model regularization. In current practice, ϕ[sub m] is posed as a mathematical operator that potentially includes limited prior information on the model, m. This research focusses on the specification of learned forms of

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