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Approximation of discontinuous inverse operators with neural networks

Massa, Paolo; Benvenuto, Federico; Garbarino, Sara

In this work we deal with parametric inverse problems, which consist in recovering a finite number of parameters describing the structure of an unknown object, from indirect measurements. State-of-the-art methods for approximating a regularizing inverse operator by using a dataset of input-output pairs of the forward model rely on deep learning te…