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We present an optimization-based framework to construct confidence intervals for functionals in constrained inverse problems, ensuring …
Preprint

Through the Bayesian lens of data assimilation, uncertainty on model parameters is traditionally quantified through the posterior …
Preprint

Unfolding is an ill-posed inverse problem in particle physics aiming to infer a true particle-level spectrum from smeared …
Preprint Code DOI

Uncertainty quantification (UQ) is, broadly, the task of determining appropriate uncertainties to model predictions. There are …
Preprint Code DOI