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Inverse problems are typically concerned with the interpretation of indirectly measured data that are related to the quantities of interest (images) through models that describe the data acquisition. In practice, one has to deal not only with noisy or incomplete data, but also with simplified or imperfect models that cannot capture the mechanisms of data acquisition in full complexity. Correctly accounting for these imperfections is crucial for the development of stable numerical algorithms. The aim of this workshop is bringing together researchers working on different approaches to such problems arising in imaging in order to highlight similarities as well as differences and foster further collaboration.