marginalized out you can use denoising auto-encoders to estimate the required gradient but to make the denoising auto-encoder create really good images the auto encoder needs to be trained with several different losses one of those losses is the adversarial networks loss and that forces it to make images that look very realistic as well as images that are close to the original data in l2 space this confirms some of the tips that I gave earlier in the talk for example on the tips and tricks section I said that you often get much