Denoising autoencoders have the ability to reconstruct corrupted data. DAEs are a stochastic version of vanilla AE that randomly corrupts the input, hence introducing noise, that the AE must learn to reconstruct. Therefore, instead of having the output be similar to the input, the system is trained to make the outputs denoised and “cleaner”.
