# Denoising Autoencoder

> Source: https://sukruyusufkaya.com/en/glossary/denoising-autoencoder
> Updated: 2026-05-13T20:56:42.883Z
> Type: glossary
> Category: derin-ogrenme
**TLDR:** A type of autoencoder that learns more robust representations by reconstructing clean outputs from corrupted inputs.

<p>A denoising autoencoder is trained by feeding the model corrupted or noisy data while asking it to reconstruct the original clean structure. This encourages the model to learn not only compression, but also robust representations. It is valuable for denoising, data cleaning, and building stronger latent features. It becomes especially useful when real-world data is noisy, incomplete, or imperfect.</p>