Neural Message Passing

Neural Message Passing is a technique in machine learning that helps computers understand complex structures like molecules or networks. It works by having each part (node) of the structure exchange information, or "messages," with its neighbors. These messages update each node's understanding based on its connections. Repeating this process allows the system to capture intricate relationships within the structure, enabling tasks like predicting properties or behaviors. Essentially, it’s a way for a neural network to learn and reason about interconnected systems by iteratively sharing and updating information.