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eess.IV2025
Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements
Tom Sprunck, Marcelo Pereyra, Tobias Liaudat
Modern imaging techniques heavily rely on Bayesian statistical models to address difficult image reconstruction and restoration tasks. This paper addresses the objective evaluation…
eess.IV2025
DeepInverse: A Python package for solving imaging inverse problems with deep learning
Julián Tachella, Matthieu Terris, Samuel Hurault +24
DeepInverse is an open-source PyTorch-based library for solving imaging inverse problems. The library covers all crucial steps in image reconstruction from the efficient implementa…