Variational Autoencoders (VAEs) are an artificial neural network architecture to generate new data. They are similar to regular autoencoders, which consist of an encoder and decoder. The encoder takes ...
The objective of this project is to detect anomalies in high-dimensional data using a Variational Autoencoder (VAE). The model is trained only on normal data and anomalies are identified based on ...
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