Reference 3 stops to get here

Message Passing

The fundamental operation in GNNs where nodes exchange and aggregate information with neighbors.

Your route here

3 stops · basics first
  1. Machine Learning ✓ understood

    Building systems that learn patterns from data instead of following hand-written rules, getting better at a task as they see more examples.

  2. Neural Network ✓ understood

    A computational model inspired by biological neural networks, consisting of interconnected nodes (neurons) organized in layers that process information through weighted connections.

  3. Graph Neural Network ✓ understood

    Neural networks designed to operate on graph-structured data, learning representations of nodes, edges, and entire graphs.

  4. Message Passing · you are here ✓ understood

The fundamental operation in GNNs where nodes exchange and aggregate information with neighbors.

This concept is essential for understanding emerging & advanced and forms a key part of modern AI systems.

  • GNN
  • Graph Learning
  • Aggregation

Where it sits

Before this

Graph Neural Network
Message Passing

Leads to

Nothing yet: a destination in its own right.

Explore nearby

Neural Networks Graph Attention Network A GNN using attention mechanisms to weight neighbor contributions when aggregating information. Neural Networks Node Embedding Learning vector representations of graph nodes that capture structural and feature information. Foundations Knowledge Graph A structured representation of knowledge as entities and their relationships, used for reasoning and information retrieval. Language & LLMs Embedding A list of numbers (a vector) that represents a word, sentence, image or other item, learned so that similar items end up close together.