Variational Autoencoder (VAE) is a type of generative machine learning model that combines elements of neural networks and Bayesian inference. VAE

Autoencoder (AE) is an artificial neural network architecture primarily used for the task of data encoding and decoding. The structure of AE

Multi-Layer Perceptron (MLP) is a type of artificial neural network, composed of multiple layers of neurons, where each layer is fully connected to the previous layer.

The Self-Organizing Map (SOM) is a type of unsupervised artificial neural network introduced by Teuvo Kohonen. SOM is used to

A Restricted Boltzmann Machine (RBM) is a type of unsupervised probabilistic model, a subset of neural networks, that is used to learn representations of

A Deep Belief Network (DBN) is a type of deep learning model composed of multiple layers that learn data representation in a

Conditional Random Fields (CRFs) are a type of statistical model from the family of graphical models that are primarily used for sequence of events tasks.

Hidden Markov Models (HMM) are a class of statistical models used to represent sequences of observations, where the process

A Knowledge Graph (KG) is a data structure that represents information in graph form, where nodes represent entities.

Knowledge Representation (KR) is a field of artificial intelligence and computer science that focuses on the design of data structures and algorithms for

Information Extraction (IE) is an area of artificial intelligence and natural language processing that focuses on identifying, extracting and structuring

Information Retrieval (IR) is the field of computer science that focuses on developing methods and techniques for searching, retrieving, and presenting information.