Graph Neural Network
A Graph Neural Network (GNN) is a class of artificial neural network designed to process data represented as graphs (consisting of nodes and edges), extracting features through message-passing neighborhoods.
Frequently Asked Questions
What is message passing in a GNN?▼
The process where nodes aggregate feature information from their neighboring nodes and edges to update their own representation state.
Why are GNNs needed for graph data instead of standard networks?▼
Standard networks assume grid structures (like images) or sequences (like text). Graph data is non-Euclidean with variable connections, requiring permutation-invariant operations.
Quick Facts
- CategoryNeural Architectures
- Key ApplicationMolecular drug discovery, social network connection maps, and recommendation graphs.
Coverage Trend12 Weeks
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