look like feed-forward neural networks goes this was a standard recipe to even do supervised learning back then because you needed some reasonably high level features to operate well to train a good supervised model so here are the filters that you learn with a denoising auto-encoder for various levels of noises and you can clearly see that the ones where you actually add more noise is learning more of these digit edges whereas the ones you don't have any noise you're hardly learning anything because it's mostly gonna do an identity