| Towards Automatic Concept-based Explanations | Feb 7, 2019 | Feature Importance | CodeCode Available | 0 |
| Classification-Specific Parts for Improving Fine-Grained Visual Categorization | Sep 16, 2019 | ClassificationFeature Importance | CodeCode Available | 0 |
| Automated Dynamic Bayesian Networks for Predicting Acute Kidney Injury Before Onset | Apr 20, 2023 | Feature Importance | CodeCode Available | 0 |
| Automated discovery of symbolic laws governing skill acquisition from naturally occurring data | Apr 8, 2024 | Feature ImportanceSymbolic Regression | CodeCode Available | 0 |
| I Bet You Did Not Mean That: Testing Semantic Importance via Betting | May 29, 2024 | Feature Importanceimage-classification | CodeCode Available | 0 |
| Identification of Twitter Bots Based on an Explainable Machine Learning Framework: The US 2020 Elections Case Study | Dec 8, 2021 | Feature ImportanceTwitter Bot Detection | CodeCode Available | 0 |
| The Impact of Feature Quantity on Recommendation Algorithm Performance: A Movielens-100K Case Study | Jul 13, 2022 | AutoMLFeature Importance | CodeCode Available | 0 |
| The Impact of Feature Representation on the Accuracy of Photonic Neural Networks | Jun 26, 2024 | Feature Importance | CodeCode Available | 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 |
| Rule induction for global explanation of trained models | Aug 29, 2018 | Feature Importancetext-classification | CodeCode Available | 0 |
