The visualizations of image gradients was really fascinating, I never really thought about plotting the gradient of each pixel channel as an image. I take it these gradients are for a particular (and same) random starting value and step size? It's not totally clear.
(I have to say, "second-to-last figure.." again.. cool presentation but being able to say "figure 9" or whatever would be nice. Not everything about traditional publication needs to be thrown out the window.. figure and section numbers are useful for discussion!)
When we do feature visualization we do start from a random point/noise. For the diagram showing steepest descent directions, however, the gradient is evaluated on an input image from the dataset, shown as the leftmost image.
There's no real step size either as we're showing the direction. You can think of the scale as arbitrary and chosen for appearance.
Section numbers are on their way—and figure numbers also sound helpful! I've added a ticket. (https://github.com/distillpub/template/issues/63)
For now you can already link to figures like this: https://distill.pub/2017/feature-visualization/#steepest-des...