Automated Reasoning

Autoencoders are neural networks designed to compress input data into a smaller, latent representation and then reconstruct the original data from this compressed form. They are commonly used for feature extraction, dimensionality reduction, and data denoising. Autoencoders learn efficient codings by minimizing the difference between the input and output, enabling applications in unsupervised learning, anomaly detection, and data compression.