About this document
Variational Autoencoders and GANs Explained by Kavitha is a document available to read on EtoBox.
The document discusses Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) as deep generative models. VAEs utilize an encoder-decoder architecture to learn the underlying data distribution and generate new samples, while GANs consist of a Generator and Discriminator that compete to produce realistic data. Both models are widely used for tasks like data generation and pattern recognition in various domains.
- Author
- Kavitha
- Language
- EN