PearSAN: A Machine Learning Method for Inverse Design using Pearson
Correlated Surrogate Annealing
PearSAN: A Machine Learning Method for Inverse Design using Pearson
Correlated Surrogate Annealing
PearSAN is a machine learning-assisted optimization algorithm applicable to inverse design problems with large design spaces, where traditional optimizers struggle. The algorithm leverages the latent space of a generative model for rapid sampling and employs a Pearson correlated surrogate model to predict the figure of merit of the true design …