ATAIS is an adaptive importance sampler that alternates between sampling nonlinear-model parameters and analytically updating the noise covariance matrix, then reweights old samples to approximate the joint posterior over both.
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Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals
ATAIS is an adaptive importance sampler that alternates between sampling nonlinear-model parameters and analytically updating the noise covariance matrix, then reweights old samples to approximate the joint posterior over both.