Variational Autoencoder (VAE)
Neural Networks
Generative model learning latent representations
What is Variational Autoencoder (VAE)?
Encodes data to latent distribution, samples from it, decodes. Can generate new similar data.
Real-World Examples
- •Generating new faces
- •Image interpolation
- •Anomaly detection
When to Use This
For learning meaningful latent representations and generation
Related Terms
Learn more about concepts related to Variational Autoencoder (VAE)