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The left-most column consists of a random sample of hand-written digits from the test set. The other columns are analogies generated from the learned model p(x|z,y). The writing style ('z') of each generated row is inferred from the test-set image in the left-most column, while the class label ('y') iterates from [0,...,9] from left to right. We think this success is quite exciting, and that it accentuates a big advantage of the fully probabilistic approach: the ability to perform meaningful inferences on which the model was not explicitly trained.