Definition
Latent space is the internal representation where neural networks encode meaningful features of data in a lower-dimensional form.
Key Concepts: - Compressed representation of input - Captures underlying structure - Enables generation and manipulation - Learned during training
Properties: - Dimensionality reduction - Semantic organization - Interpolation between points - Clustering of similar items
Applications: - Image generation (VAE, GAN, Diffusion) - Representation learning - Anomaly detection - Style transfer
Visualization: - t-SNE - UMAP - PCA
Similar concepts often cluster together in latent space, enabling meaningful operations like "king - man + woman = queen".
Examples
Moving through Stable Diffusion's latent space to morph between a cat and a dog image.
Related Terms
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