Pierre Chainais
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126
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Stats Method.×1Signal Processing×1
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2026
A Hierarchical Likelihood Model for Non-linear Inverse Problems under Additive and Multiplicative Noise
This paper proposes a hierarchical Bayesian model and an efficient MCMC algorithm to tackle ill-posed inverse problems in the presence of non-linear forward models, additive and multiplicative noise, and censored data.
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