There and back again: revisiting backpropagation saliency methods
Saliency methods seek to explain the predictions of a model by producing an importance map across each input sample. A popular class of such methods is based on backpropagating a signal and analyzing the resulting gradient. Despite much research on such methods, relatively little work has been done...
| Автори: | , , , |
|---|---|
| Формат: | Conference item |
| Мова: | English |
| Опубліковано: |
IEEE
2020
|