Variational Autoencoders Pursue PCA Directions (by Accident)

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Rolinek, Michal; Zietlow, Dominik; Martius, Georg;
  • Subject: Computer Science - Computer Vision and Pattern Recognition | Statistics - Machine Learning | Computer Science - Machine Learning

The Variational Autoencoder (VAE) is a powerful architecture capable of representation learning and generative modeling. When it comes to learning interpretable (disentangled) representations, VAE and its variants show unparalleled performance. However, the reasons for ... View more
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