Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview

Code

• github.com/alexanderauras/gamm-overview-23
  OfficialIn paperpytorch★ 1

Abstract

This paper provides an overview of current approaches for solving inverse problems in imaging using variational methods and machine learning. A special focus lies on point estimators and their robustness against adversarial perturbations. In this context results of numerical experiments for a one-dimensional toy problem are provided, showing the robustness of different approaches and empirically verifying theoretical guarantees. Another focus of this review is the exploration of the subspace of data-consistent solutions through explicit guidance to satisfy specific semantic or textural properties.

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