論文筆記understanding black-box predictions via influence functions
Purpose **To formalize the impact of a training point on a prediction, we ask the counterfactual: what would happen if we did not have this training point, or if the values of this training point were
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相關文章
- 1. （2017ICML Bestpaper）Understanding Black-box Predictions via Influence Functions 筆記
- 2. 論文淺嘗 | Understanding Black-box Predictions via Influence Func
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- 4. 論文筆記Visualizing and understanding convolutional networks
- 5. 《Understanding Convolution for Semantic Segmentation》論文筆記
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- 7. Understanding Neural Networks Through Deep Visualization 論文筆記
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