Variational Autoencoder
A Variational Autoencoder (VAE) is a generative neural network architecture, introduced by Diederik Kingma and Max Welling in 2013, that learns to compress data into a probabilistic, continuous latent representation and then reconstruct or generate new data from that representation, combining ideas from autoencoders…
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Glossary Terms(6)
GAN
A Generative Adversarial Network (GAN) is a machine learning framework, introduced by Ian Goodfellow and colleagues in 2014, in which two neural networks — a g…
Variational Autoencoder (VAE)
A Variational Autoencoder (VAE) is a generative neural network architecture, introduced by Diederik Kingma and Max Welling in 2013, that learns to compress dat…
Dimensionality Reduction
Dimensionality reduction is the process of transforming data with many input variables into a lower-dimensional representation that preserves as much meaningfu…
Autoencoder
An autoencoder is a type of neural network trained to reconstruct its own input by first compressing it into a smaller latent representation (encoding) and the…
Variational Autoencoder
A Variational Autoencoder (VAE) is a generative neural network that learns a probabilistic latent representation of data, enabling it to both reconstruct input…
Generative Adversarial Network
A Generative Adversarial Network (GAN) is a generative modeling framework in which two neural networks — a generator and a discriminator — are trained in compe…