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cs.LG2019
Quantization-Based Regularization for Autoencoders
Hanwei Wu, Markus Flierl
Autoencoders and their variations provide unsupervised models for learning low-dimensional representations for downstream tasks. Without proper regularization, autoencoder models a…
cs.LG2018
Variational Information Bottleneck on Vector Quantized Autoencoders
Hanwei Wu, Markus Flierl
In this paper, we provide an information-theoretic interpretation of the Vector Quantized-Variational Autoencoder (VQ-VAE). We show that the loss function of the original VQ-VAE ca…