Which type of autoencoder is designed specifically for generating data that is similar but not identical to the training data?
- Variational Autoencoder
- Denoising Autoencoder
- Contractive Autoencoder
- Sparse Autoencoder
Variational Autoencoders (VAEs) are designed for generating data that is similar but not identical to the training data. They generate data from a learned distribution, enabling the generation of new and similar data points by sampling from this distribution.
Loading...
Related Quiz
- What is the primary goal of exploration in reinforcement learning?
- In which learning approach does the model learn to make decisions by receiving rewards or penalties for its actions?
- Which term refers to using a model that has already been trained on a large dataset and fine-tuning it for a specific task?
- When training a robot to play a game where it gets points for good moves and loses points for bad ones, which learning approach would be most appropriate?
- How does the architecture of a CNN ensure translational invariance?