Akiko Kumada

State-Constrained SHAP Distills Polymer Property Models into Transferable Structural Rules for Fixed-Interval Screening

Abstract Polymer informatics has accelerated data-driven prediction of polymer properties, yet accurate prediction does not directly enable discovery. Here, we introduce state-constrained SHAP (SC-SHAP), an attribution-to-rule distillation framework for fixed-interval polymer scr...

Interpretable substructure-based screening of multi-property polymer dielectrics with prompt-ready rules for rational design

Abstract High-performance polymer dielectrics remain difficult to discover because transparent connections between molecular substructures and macroscopic properties are lacking. Existing machine-learning approaches often rely on black-box representations that obscure the chemica...