Hi - added Guided Backprop and Grad-CAM guided backprop to the notebook. Literally three lines of code using fastai Hooks . . .
The idea is to determine the importance of each pixel to the prediction that is made by the network. To avoid interference, the backprop is clipped to positive gradient contributions. This was introduced in Striving for Simplicity: the All Convolutional Net paper.
Example output:
Element-wise multiplication with grad-cam:
And here is the notebook, also showing what happens when you just plot the gradients, without doing guided backprop.