Generative Models

AutoEncoder

Introduced by Hinton et al. in Reducing the Dimensionality of Data with Neural Networks

An Autoencoder is a bottleneck architecture that turns a high-dimensional input into a latent low-dimensional code (encoder), and then performs a reconstruction of the input with this latent code (the decoder).

Image: Michael Massi

Source: Reducing the Dimensionality of Data with Neural Networks

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🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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