Variational Autoencoder, Scanning Probe Microscope, Representation Learning, Invariance, Electron Microscopy.
are a class of neural networks developed in 2014 by Welling, Kingma, and Rezende that allow to discover the latent representations of the data. On a very superficial level, VAE compresses the high dimensional data to a low dimensional latent vector, and then learns how decode the latent vector back