Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing

no code implementations • 3 Dec 2021 • Loc Truong, Woongjo Choi, Colby Wight, Lizzy Coda, Tegan Emerson, Keerti Kappagantula, Henry Kvinge

We show that by focusing on the experimenter's need to choose between multiple candidate experimental parameters, we can reframe the challenging regression task of predicting material properties from processing parameters, into a classification task on which machine learning models can achieve good performance.

BIG-bench Machine Learning Experimental Design +1