  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.
