Belief Propagation

Belief propagation is a method used to infer or update information in complex systems, such as networks or graphical models. Imagine a group of friends sharing opinions about a movie. Each friend considers their own view and adjusts it based on what their friends say. Similarly, in belief propagation, nodes (like friends) exchange and update beliefs (opinions) about certain variables (like movie ratings) in a network, gradually leading to a consistent set of beliefs across the whole network. This technique is widely used in fields like computer vision, machine learning, and error correction in communications.