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math.NA2022★ 2 cited
Efficient Derivative-free Bayesian Inference for Large-Scale Inverse Problems
Daniel Zhengyu Huang, Jiaoyang Huang, Sebastian Reich +1
We consider Bayesian inference for large scale inverse problems, where computational challenges arise from the need for repeated evaluations of an expensive forward model. This ren…
math.NA2021★ 2 cited
Unscented Kalman Inversion: Efficient Gaussian Approximation to the Posterior Distribution
Daniel Z. Huang, Jiaoyang Huang
The unscented Kalman inversion (UKI) method presented in [1] is a general derivative-free approach for the inverse problem. UKI is particularly suitable for inverse problems where…
math.NA2021★ 4 cited
Improve Unscented Kalman Inversion With Low-Rank Approximation and Reduced-Order Model
Daniel Z. Huang, Jiaoyang Huang
The unscented Kalman inversion (UKI) presented in [1] is a general derivative-free approach to solving the inverse problem. UKI is particularly suitable for inverse problems where…