Interpretability

On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)

Principal component analysis: a review and recent developments

A Unified Approach to Interpreting Model Predictions

A survey of methods for explaining black box models

fMRIPrep: a robust preprocessing pipeline for functional MRI

A review on the attention mechanism of deep learning

On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)

Advances in the Application of Machine Learning in Composite Materials

Applications of machine learning in materials science: From a methodological point of view

Feature Engineering Enhanced Machine Learning Prediction of Pore Properties in Lignin-Derived Nanoporous Carbon for High-Performance Supercapacitor Applications

Machine learning–driven thermoelectric materials: Review on prediction, optimization, and discovery

Machine Learning Predictions of Thermopower for Thermoelectric Material Screening