A composition-weighted symbolic regression framework learns analytical expressions and elemental weightings from composition to predict materials properties with accuracy competitive to black-box models while producing explicit, constraint-enforcing formulas.
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Composition-Weighted Symbolic Regression for General-Purpose Property Prediction
A composition-weighted symbolic regression framework learns analytical expressions and elemental weightings from composition to predict materials properties with accuracy competitive to black-box models while producing explicit, constraint-enforcing formulas.