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Stacked Wasserstein Autoencoder

The proposed model is built on the theoretical analysis presented in [30,14]. Similar to the ARAE [14], our model provides flexibility in learning an autoencoder from the input space at the first stage.

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Cite this as

Wenju Xu, Shawn Keshmiri, Guanghui Wang (2024). Dataset: Stacked Wasserstein Autoencoder. https://doi.org/10.57702/zona57lw

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.1910.02560
Author	Wenju Xu
More Authors	Shawn Keshmiri Guanghui Wang
Homepage	https://arxiv.org/abs/1909.00114