M. S. Kim

Uncertainty quantification and parameter optimization of a plasma etching process using a heteroscedastic Gaussian process

This study presents an uncertainty-aware framework for the reliability-based robust design optimization (RBRDO) of plasma etching processes in semiconductor manufacturing. The framework is demonstrated using experimental measurements of the remaining thickness collected at nine w...

Assessing quantum advantage for Gaussian process regression

Abstract Gaussian Process Regression is a machine learning technique with established applications for which several quantum algorithms have been proposed. We show here that in a wide range of scenarios these algorithms show no exponential speedup. We achieve this by rigorously p...