OpenAI has published research on a Variational Autoencoder (VAE) that combines VAEs with autoregressive models like RNNs and PixelCNNs. This new VAE architecture allows for control over what the latent code learns, enabling it to discard irrelevant information such as texture in images. The model achieves state-of-the-art results on density estimation tasks for MNIST, OMNIGLOT, and Caltech-101 Silhouettes. AI
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RANK_REASON The cluster contains an academic paper from a notable AI research lab.
