Zoom Link: https://umich.zoom.us/j/97823527756?pwd=H01BbvtuG5q02Wzb8LJvhUnvijlAIe.1 Abstract: This talk focuses on a derivative-informed supervised learning method for efficiently building machine learning surrogates of high-fidelity computational models, particularly those governed by parametric partial differential equations. Unlike the conventional supervised learning method that treats the model as a black box, our approach leverages additional model sensitivity information, extracted via solving […]