Nota: A tradução desta entrada está atualmente em revisão de qualidade, portanto parte do conteúdo é exibida temporariamente apenas em inglês.
Este verbete ainda não foi traduzido para o seu idioma, portanto o original é exibido abaixo.
latent space
This term is primarily used in machine learning and statistics to describe a hidden representation of data. It refers to a lower-dimensional space where the distance between points reflects semantic similarity rather than raw pixel or token similarity. For example, in a latent space for faces, two different images of the same person would be positioned close together despite having different pixel values.
Because it is a technical term from mathematics and computer science, it is almost exclusively used in formal, academic, or professional technical contexts. It is rarely used in general conversation unless discussing artificial intelligence or data dimensionality reduction.
Meanings
A compressed, lower-dimensional representation of data where hidden features are captured.
Examples
The model maps the high dimensional input into a compact latent space.
We can interpolate between two points in the latent space to generate a smooth transition.
I wonder if the latent space has captured the underlying structure of the images.
Let us analyze how the latent space organizes these different categories of data.
The autoencoder compresses the data into a latent space before reconstructing it.
By manipulating the latent space, we can change specific attributes of the generated face.
Is the latent space too small to represent all the necessary features?
The latent space provides a simplified representation of complex real world patterns.