Theory guided machine learning in material science
Amit Rai
Theory-Guided Machine Learning in Materials Science of overfitting to training data using decision trees as an example, rational descriptor selection in the field of perovskites, and preserving physical interpretability in the application of dimensionality reducing techniques such as principal component analysis. We show how proceeding without the guidance of domain knowledge can lead to both quantitatively and qualita- tively incorrect predictive models.
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Quantam Computing Publication