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Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Apply RSP instead of other fully decomposed attribution methods | VGG-16 · PASCAL VOC 2007, predicted classes | Pointing Game: RSP .946; c*RSP .881 | Mixed |
| Use contrastive initialization for the relative gradient map (ablation) | RSP on PASCAL VOC 2007 · PASCAL VOC 2007, predicted classes | Pointing Game: .946 -> .881 | Hurt |
| Use contrastive initialization for the relative gradient map (ablation) | RSP on PASCAL VOC 2007 · PASCAL VOC 2007, predicted classes | Pointing Game: .909 -> .949 | Helped |
| Use contrastive initialization for the relative gradient map (ablation) | RSP on COCO 2014 · COCO 2014 validation, predicted classes | Pointing Game: .725 -> .675; .688 -> .697 | Mixed |
| Add CRF refinement to RSP | RSP · ImageNet Segmentation | mIoU: 60.81 -> 64.51 | Helped |
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