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arXiv · 1812.02769

Embedding-reparameterization procedure for manifold-valued latent variables in generative models

Eugene Golikov·Maksim Kretov
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Abstract

Conventional prior for Variational Auto-Encoder (VAE) is a Gaussian distribution. Recent works demonstrated that choice of prior distribution affects learning capacity of VAE models. We propose a general technique (embedding-reparameterization procedure, or ER) for introducing arbitrary manifold-valued variables in VAE model. We compare our technique with a conventional VAE on a toy benchmark problem. This is work in progress.

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Eugene Golikov, Maksim Kretov. 2018-12-06. Embedding-reparameterization procedure for manifold-valued latent variables in generative models. https://arxiv.org/abs/1812.02769

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