r/MachineLearning - [D] If you had to show one paper to someone to show that machine learning is beautiful, what would you choose? (assuming they're equipped to understand it)

The graphs are related to the dimensionality reduction. The experiment is try to reduce the dimensionality of MNIST dataset (set of images of hand-drawn digits) as much as possible without loosing their separability in the lower dimensional space. On the right is algorithm PCA which reduces the dimension by eliminating the directions which have less variance and then projecting the data on the remaining dimensions. On the left is auto-encoder (think it like a neural network same number of nodes at input and output layers, but very few at the middle, 2 in this case) which feeds the image at input layer and expect the same image at output layer, but near the middle of the network, the number of layers are drastically reduced, thus creating a squeezing kind of process, or information bottleneck kind of phenomenon. The magic is in the output.