What is graphical models?

Graphical models are probabilistic models for which a graph expresses the conditional dependence structure between random variables. They are commonly used in machine learning, statistics, and computer vision to represent and reason about complex systems. These models allow for efficient computation and inference by exploiting the relationships of conditional independence encoded in the graph structure. Common types include Bayesian networks (directed graphs) and Markov networks (undirected graphs).