Deep ensemble neural network-driven modeling of etching process in advanced integrated circuit manufacturing
An autonomous modeling method based on deep ensemble neural networks to construct a high-fidelity physical etching model that can automatically extract and calibrate key model parameters using significantly less experimental data, to achieve predicted profiles that are in excellent agreement with experiments.