| Calibrated Explanations for Regression | Aug 30, 2023 | counterfactualExplainable artificial intelligence | CodeCode Available | 1 |
| Calibrated Explanations: with Uncertainty Information and Counterfactuals | May 3, 2023 | counterfactualExplainable artificial intelligence | CodeCode Available | 1 |
| Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | Nov 2, 2020 | Feature ImportancePerson Re-Identification | CodeCode Available | 1 |
| Compressing Features for Learning with Noisy Labels | Jun 27, 2022 | Feature CompressionFeature Importance | CodeCode Available | 1 |
| Benchmarking Deep Learning Interpretability in Time Series Predictions | Oct 26, 2020 | BenchmarkingDeep Learning | CodeCode Available | 1 |
| CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models | Dec 6, 2023 | Feature ImportancePhilosophy | CodeCode Available | 1 |
| Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud | Sep 7, 2021 | Bias DetectionBIG-bench Machine Learning | CodeCode Available | 1 |
| A Matlab Toolbox for Feature Importance Ranking | Mar 10, 2020 | Feature Importancefeature selection | CodeCode Available | 1 |
| A Unified Approach to Interpreting Model Predictions | May 22, 2017 | Feature ImportanceImage Attribution | CodeCode Available | 1 |
| agtboost: Adaptive and Automatic Gradient Tree Boosting Computations | Aug 28, 2020 | Feature Importance | CodeCode Available | 1 |
