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Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements

arXiv — cs.LG•Monday, November 3, 2025 at 5:00:00 AM
NeutralArtificial Intelligence

Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements

A recent paper discusses the use of Bayesian statistical models in modern imaging techniques, particularly for image reconstruction and restoration tasks. It highlights the challenges of evaluating these models when ground truth data is not available, focusing on model selection and diagnosing misspecification. This research is significant as it addresses the limitations of current unsupervised evaluation methods, which can be computationally expensive and impractical for imaging applications.
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