| RISE: Randomized Input Sampling for Explanation of Black-box Models | Jun 19, 2018 | Explainable Artificial Intelligence (XAI)Feature Importance | CodeCode Available | 1 |
| A Unified Approach to Interpreting Model Predictions | May 22, 2017 | Feature ImportanceImage Attribution | CodeCode Available | 1 |
| Axiomatic Attribution for Deep Networks | Mar 4, 2017 | Explainable artificial intelligenceImage Attribution | CodeCode Available | 1 |
| Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization | Oct 7, 2016 | General ClassificationImage Attribution | CodeCode Available | 1 |
| "Why Should I Trust You?": Explaining the Predictions of Any Classifier | Feb 16, 2016 | Image Attributionimage-classification | CodeCode Available | 1 |
| IBO: Inpainting-Based Occlusion to Enhance Explainable Artificial Intelligence Evaluation in Histopathology | Aug 29, 2024 | ClassificationDenoising | CodeCode Available | 0 |
| Explainable Deep Learning: A Visual Analytics Approach with Transition Matrices | Mar 29, 2024 | Deep LearningExplainable Artificial Intelligence (XAI) | CodeCode Available | 0 |
| Improving Interpretability via Regularization of Neural Activation Sensitivity | Nov 16, 2022 | Adversarial RobustnessExplanation Fidelity Evaluation | —Unverified | 0 |
| A Semi-supervised Deep Transfer Learning Approach for Rolling-Element Bearing Remaining Useful Life Prediction | Sep 29, 2021 | Interpretability Techniques for Deep LearningManagement | CodeCode Available | 0 |
| A deep supervised learning approach for condition-based maintenance of naval propulsion systems Tarek | Dec 29, 2020 | Interpretability Techniques for Deep Learning | —Unverified | 0 |
