AI Dictionary
Latent Space
Definition
An abstract multi-dimensional space containing feature values that we cannot interpret directly.
Deep Dive
A latent space, also known as an embedding space, is an abstract, typically lower-dimensional, multi-dimensional space created by machine learning models to represent the underlying structure and essential features of high-dimensional data. In this compressed representation, data points that are semantically or structurally similar in the original high-dimensional space are mapped closer together, while dissimilar points are further apart.
Examples & Use Cases
- 1The compressed representation of an image in an autoencoder, allowing for efficient storage or manipulation of its key features
- 2Word embeddings (e.g., Word2Vec) where words are mapped to vectors in a latent space, and semantically similar words are close to each other
- 3Navigating the latent space of a Generative Adversarial Network (GAN) to create novel, realistic images that share characteristics of the training data
Related Terms
Dimensionality ReductionFeature EngineeringEmbedding