An encoder or generative model maps observations to latent vectors that support reconstruction, similarity, or controlled variation. Individual dimensions are not guaranteed to correspond cleanly to human concepts.
A latent space is an internal representation space whose dimensions encode learned factors or patterns in data.
An encoder or generative model maps observations to latent vectors that support reconstruction, similarity, or controlled variation. Individual dimensions are not guaranteed to correspond cleanly to human concepts.