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Use of Student's t-Distribution for the Latent Layer in a Coupled Variational Autoencoder

Machine Learning 2020-11-24 v1 Information Theory math.IT

Abstract

A Coupled Variational Autoencoder, which incorporates both a generalized loss function and latent layer distribution, shows improvement in the accuracy and robustness of generated replicas of MNIST numerals. The latent layer uses a Student's t-distribution to incorporate heavy-tail decay. The loss function uses a coupled logarithm, which increases the penalty on images with outlier likelihood. The generalized mean of the generated image's likelihood is used to measure the performance of the algorithm's decisiveness, accuracy, and robustness.

Keywords

Cite

@article{arxiv.2011.10879,
  title  = {Use of Student's t-Distribution for the Latent Layer in a Coupled Variational Autoencoder},
  author = {Kevin R. Chen and Daniel Svoboda and Kenric P. Nelson},
  journal= {arXiv preprint arXiv:2011.10879},
  year   = {2020}
}

Comments

8 pages, 3 figures, 1 table