A VAE trained with a hand-built hyperspherical-coordinate regularizer compresses latent codes into a small region of the sphere and appears to improve decoded sample quality, though the reported generation protocol uses a distribution fitted to test latents.
Why do Variational Autoencoders Really Promote Disentanglement?
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Improving the Generation of VAEs with High Dimensional Latent Spaces by the use of Hyperspherical Coordinates
A VAE trained with a hand-built hyperspherical-coordinate regularizer compresses latent codes into a small region of the sphere and appears to improve decoded sample quality, though the reported generation protocol uses a distribution fitted to test latents.