Dueling Decoders: Regularizing Variational Autoencoder Latent Spaces

Variational autoencoders learn unsupervised data representations, but these models frequently converge to minima that fail to preserve meaningful semantic information. For example, variational autoencoders with autoregressive decoders often collapse into autodecoders, where they learn to ignore the...

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Hauptverfasser:	Seybold, Bryan, Fertig, Emily, Alemi, Alex, Fischer, Ian
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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