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SotA/Miscellaneous/Interpretability Techniques for Deep Learning/CelebA

Interpretability Techniques for Deep Learning on CelebA

Metric: Insertion AUC score (higher is better)

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#Model↕Insertion AUC score▼Extra DataPaperDate↕Code
1RISE0.5703NoRISE: Randomized Input Sampling for Explanation ...2018-06-19Code
2HSIC-Attribution0.5692NoMaking Sense of Dependence: Efficient Black-box ...2022-06-13Code
3Kernel SHAP0.5246NoA Unified Approach to Interpreting Model Predict...2017-05-22Code
4LIME0.5246No"Why Should I Trust You?": Explaining the Predic...2016-02-16Code
5Saliency0.4632NoDeep Inside Convolutional Networks: Visualising ...2013-12-20Code
6Grad-CAM0.3721NoGrad-CAM: Visual Explanations from Deep Networks...2016-10-07Code
7Integrated Gradients0.3578NoAxiomatic Attribution for Deep Networks2017-03-04Code