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Bad Apple!! but it's learned by a Vector Quantized Variational Autoencoder for reconstruction.
3:40
YouTubeComputeIQ
Bad Apple!! but it's learned by a Vector Quantized Variational Autoencoder for reconstruction.
A Vector Quantized Variational Autoencoder (VQ-VAE) is an application of machine learning which leverages a mechanism called vector quantization to map continuous latent representations into discrete embeddings. The purpose of the VQ-VAE is to learn a meaningful compressed representation of our original data. There ...
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