What are autoencoders in dimensionality reduction?

Autoencoders are neural networks that learn compressed representations of data.

An autoencoder consists of encoder and decoder networks. The encoder compresses input into a latent space, and the decoder reconstructs it. Training minimizes reconstruction loss.