Results 191 to 200 of about 30,731 (301)

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

open access: yesAdvanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang   +3 more
wiley   +1 more source

Mathematical modeling of tumor nanomechanical fingerprints: A weighted skew-normal distribution approach for cancer diagnosis and treatment monitoring

open access: diamond
Stylianos Vasileios Kontomaris   +4 more
openalex   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

open access: yesAdvanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik   +6 more
wiley   +1 more source

A Flexible Skew-Generalized Normal Distribution [PDF]

open access: hybrid, 2015
Wahab Bahrami, Ehsan Qasemi
openalex   +1 more source

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