Architecture

Autoencoder

Definition

A neural network trained to compress data into a lower-dimensional latent space and reconstruct it. Autoencoders are used for anomaly detection, dimensionality reduction, and as components in generative models like VAEs.

Related Terms

Encoder-Decoder

A two-part neural network architecture where the encoder compresses an input into a latent representation and the decoder generates an output from it. Used in translation, summarisation, and speech recognition systems.

Diffusion Model

A class of generative models that learn to reverse a gradual noise-addition process to produce high-quality images, audio, or video from random noise. Diffusion models power leading image generators such as Stable Diffusion and DALL-E 3.

Unsupervised Learning

A machine learning approach that discovers structure in unlabelled data. Common techniques include clustering (grouping similar items) and dimensionality reduction. It is often used for anomaly detection and exploratory data analysis.

Knowing the Terms Is Step One. Applying Them Is Step Two.

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