Variational Autoencoder, Scanning Probe Microscope, Representation Learning, Invariance, Electron Microscopy.
Semi-supervised VAEs are ideally suited to solve this problem by simultaneously labelling and discovering factors of variability within the data. This is particularly powerful approach for the creation of libraries of objects observed via microscopy that can have different orientations or