autoencoders
Autoencoders are neural networks that are designed to learn how to efficiently represent and reconstruct data by compressing it into a lower-dimensional representation and then expanding it back to the original dimensions.
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Related Concepts (3)
Similar Concepts
- adversarial autoencoders
- artificial neural networks
- autoencoder layers
- encoder-decoder architecture
- encoding and decoding
- encoding and decoding techniques
- feedforward neural networks
- fractal encoding
- generative adversarial networks (gans)
- machine learning algorithms
- multilayer perceptrons
- neural encoding
- neural network architectures
- recurrent neural networks
- variational autoencoders