• Corpus ID: 247058482

Bayesian Target-Vector Optimization for Efficient Parameter Reconstruction

@inproceedings{Plock2022BayesianTO,
  title={Bayesian Target-Vector Optimization for Efficient Parameter Reconstruction},
  author={Matthias Plock and Kas Andrle and Sven Burger and Philipp-Immanuel Schneider},
  year={2022}
}
Parameter reconstructions are indispensable in metrology. Here, the objective is to to explain K experimental measurements by fitting to them a parameterized model of the measurement process. The model parameters are regularly determined by least-square methods, i.e., by minimizing the sum of the squared residuals between the K model predictions and the K experimental observations, χ 2 . The model functions often involve computationally demanding numerical simula-tions. Bayesian optimization… 
Reconstructing phase aberrations for high-precision dimensional microscopy
In many industrial sectors, dimensional microscopy enables non-destructive and rapid inspection of manufacturing processes. However, wave-optical effects and imaging errors of the optical system

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