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A Model-Informed Deep Learning Algorithm for Solving the Phaseless Inverse Scattering Problem
We study in this paper an unsupervised, two-step, model-informed deep learning framework for solving the phaseless inverse scattering problem. The objective is to reconstruct a compactly supported function that characterizes a scatterer from boundary measurements of the modulus of the total wave cor
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