Adaptive SMC with local reduced basis surrogates approximates the Gibbs posterior for PDE inverse problems, including derived error bounds and an adaptive surrogate construction strategy.
Data-driven model reduction for the Bayesian solution of inverse problems.International Journal for Numerical Methods in Engineering, 102(5):966– 990, 2015
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Adaptive particle-based approximations of the Gibbs posterior for inverse problems
Adaptive SMC with local reduced basis surrogates approximates the Gibbs posterior for PDE inverse problems, including derived error bounds and an adaptive surrogate construction strategy.