| A Survey on the Robustness of Feature Importance and Counterfactual Explanations | Oct 30, 2021 | counterfactualFeature Importance | —Unverified | 0 |
| On the explainability of hospitalization prediction on a large COVID-19 patient dataset | Oct 28, 2021 | Feature Importance | —Unverified | 0 |
| Counterfactual Shapley Additive Explanations | Oct 27, 2021 | counterfactualCounterfactual Explanation | CodeCode Available | 1 |
| Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set | Oct 26, 2021 | Additive modelsDiversity | CodeCode Available | 0 |
| ML-Based Analysis to Identify Speech Features Relevant in Predicting Alzheimer's Disease | Oct 25, 2021 | Binary ClassificationFeature Importance | —Unverified | 0 |
| Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds | Oct 25, 2021 | DiagnosticFeature Importance | CodeCode Available | 0 |
| Mechanistic Interpretation of Machine Learning Inference: A Fuzzy Feature Importance Fusion Approach | Oct 22, 2021 | BIG-bench Machine LearningDecision Making | —Unverified | 0 |
| AEFE: Automatic Embedded Feature Engineering for Categorical Features | Oct 19, 2021 | Click-Through Rate PredictionFeature Engineering | —Unverified | 0 |
| On Predictive Explanation of Data Anomalies | Oct 18, 2021 | AutoMLFeature Importance | —Unverified | 0 |
| Graph convolutional network for predicting abnormal grain growth in Monte Carlo simulations of microstructural evolution | Oct 18, 2021 | Feature ImportanceGraph Neural Network | CodeCode Available | 0 |
