Corpus ID: 209202551

A Closer Look at Disentangling in $\beta$-VAE

@article{Sikka2019ACL,
  title={A Closer Look at Disentangling in \$\beta\$-VAE},
  author={Harshvardhan Sikka and Weishun Zhong and J. Yin and Cengiz Pehlevan},
  journal={arXiv: Machine Learning},
  year={2019}
}
  • Harshvardhan Sikka, Weishun Zhong, +1 author Cengiz Pehlevan
  • Published 2019
  • Mathematics, Computer Science
  • arXiv: Machine Learning
  • In many data analysis tasks, it is beneficial to learn representations where each dimension is statistically independent and thus disentangled from the others. If data generating factors are also statistically independent, disentangled representations can be formed by Bayesian inference of latent variables. We examine a generalization of the Variational Autoencoder (VAE), $\beta$-VAE, for learning such representations using variational inference. $\beta$-VAE enforces conditional independence of… CONTINUE READING

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