The proposed approach could instead be viewed as learning a conditional denoising autoencoder which is known to capture the gradient of the logdensity.
first, the generation quality improves across all the tasks as we run more refinement steps i dec even beyond that used in training (i train = 4), which supports our interpretation as a conditional denoising autoencoder in Sec.