Autoencoder

A neural network architecture trained to compress input data into a compact representation and then reconstruct the original from that compressed form. The bottleneck in the middle forces the network to learn the most essential features of the data. Autoencoders are used for dimensionality reduction, anomaly detection, and as building blocks for more complex generative models.
See also: variational autoencoder, generative AI, latent space.