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Graph Neural Network
Neural networks designed to operate on graph-structured data, learning representations of nodes, edges, and entire graphs.
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- 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.
- 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.
- Graph Neural Network · you are here ✓ understood
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Neural Networks Message Passing The fundamental operation in GNNs where nodes exchange and aggregate information with neighbors. 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. Neural Networks Convolutional Neural Network A neural network that scans images with small learned filters, reusing the same weights at every position to build up from edges to whole objects.