The main motivation for this post was that I wanted to get more experience with both Variational Autoencoders (VAEs) and with Tensorflow. Thus, implementing the former in the latter sounded like a good idea for learning about both at the same time. This post summarizes the result.
Sparse-filtering is an unsupervised feature learning algorithms which explicitly optimizes for sparse activation of the generated feature extractors. This notebook illustrates the algorithm on the Olivetti dataset.