Unbiased estimation of the gradient of the log-likelihood in inverse problems

We consider the problem of estimating a parameter θ ∈ Θ ⊆ R d θ associated with a Bayesian inverse problem. Typically one must resort to a numerical approximation of gradient of the log-likelihood and also adopt a discretization of the problem in space and/or time. We develop a new methodology to un...

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