Technical GlossaryDeep Learning

Sparse Autoencoder

A type of autoencoder that encourages only a small number of latent neurons to activate, leading to more selective features.

A sparse autoencoder discourages all hidden units from being active all the time, encouraging the model to learn more discriminative representations. This can help produce more structured and interpretable patterns in the latent space. It is often used to improve representation quality and reduce unnecessary activation. It remains relevant in both classical representation learning and modern feature-discovery settings.