A Connection Between Score Matching and Denoising Autoencoders

A proper probabilistic model for the denoising autoencoder technique is defined, which makes it in principle possible to sample from them or rank examples by their energy, and a different way to apply score matching that is related to learning to denoise and does not require computing second derivatives is suggested.