Adversarially Regularized Autoencoders

Deep latent variable models, trained using variational autoencoders or generative adversarial networks, are now a key technique for representation learning of continuous structures. However, applying similar methods to discrete structures, such as text sequences or discretized images, has proven to be more challenging... (read more)

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Methods used in the Paper


METHOD TYPE
AutoEncoder
Generative Models