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An Autoencoder is a type of neural network model that learns compressed, encoded representations of data, usually for dimensionality reduction or feature extraction. Despite its apparent simplicity, autoencoder serves a vital role in machine learning, particularly in applications that need unsupervised learning.
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Wenen Yang (2024) studied this question.
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