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Variational autoencoder

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Revision as of 07:15, 29 January 2023 by Auntof6Bot (talk | changes) (Missing/miscoded ref display (WP ck error 3) and/or general cleanup using AWB)

In machine learning, a variational autoencoder (VAE), is an artificial neural network architecture. It was introduced by Diederik P. Kingma and Max Welling.[1]

References

  1. ↑ Kingma, Diederik P.; Welling, Max (2022-12-10). "Auto-Encoding Variational Bayes". arXiv:1312.6114 [cs, stat].


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