Inverse Problems
Autoencoders are a type of artificial neural network designed to learn efficient representations of data, typically for the purpose of dimensionality reduction or feature learning. They consist of an encoder that compresses the input into a lower-dimensional representation and a decoder that reconstructs the output from this representation, making them useful for tasks like denoising, anomaly detection, and unsupervised learning.
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