Learning Disentangled Representations with Wasserstein Auto-Encoders
Abstract: We apply Wasserstein auto-encoders (WAEs) to the problem of disentangled representation learning. We highlight the potential of WAEs with promising results on a benchmark disentanglement task.
Keywords: wasserstein auto-encoders, WAE, disentanglement
TL;DR: We apply Wasserstein Auto-encoders to the problem of disentangled representation learning
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