Architecture: Encoder compresses input to latent representation, decoder reconstructs from latent code
Training: Minimize reconstruction error. Learn meaningful compressed representations.
Latent Space: Low-dimensional representation capturing essential features
Types: Vanilla • Variational (VAE) • Denoising • Sparse • Convolutional
Applications: Dimensionality reduction • Denoising • Anomaly detection • Data compression • Feature learning