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Home/Authors/Pierre Chainais

Pierre Chainais

1 indexed paper

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26

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Stats Method.×1Signal Processing×1

Frequent co-authors

Nicolas Goeman1×
Pierre-Antoine Thouvenin1×

Research Timeline

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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Papers

stat.MEeess.SPEmpiricalRecentJul 24, 2026

A Hierarchical Likelihood Model for Non-linear Inverse Problems under Additive and Multiplicative Noise

Nicolas Goeman, Pierre-Antoine Thouvenin, Pierre Chainais

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,…

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