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... > entity > continuant > generically dependent continuant > information content entity > directive information entity > plan specification > algorithm > Neural networks models > autoencoder > denoising autoencoder

Preferred term

denoising autoencoder  

Definition

  • "Denoising autoencoders can be viewed either as a regularization option, or as robust autoencoders which can be used for error correction. In these architectures, the input is disrupted by some noise (e.g., additive white Gaussian noise or erasures using Dropout) and the autoencoder is expected to reconstruct the clean version of the input" (Bank et al., 2021).

Broader concept

Entry terms

  • DAE

Bibliographic citation(s)

  • • Bank, D., Koenigstein, N., & Giryes, R. (2021). Autoencoders (arXiv:2003.05991). arXiv. doi:10.48550/arXiv.2003.05991
  • • Vincent, P., Larochelle, H., Bengio, Y., & Manzagol, P.-A. (2008). Extracting and composing robust features with denoising autoencoders. Proceedings of the 25th International Conference on Machine Learning - ICML ’08, 1096‑1103. doi:10.1145/1390156.1390294

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URI

http://data.loterre.fr/ark:/67375/LTK-N4NJQ7FF-M

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