Abstract: Graph Attention Networks (GAT) is a type of neural network architecture designed to effectively model and process data represented as graphs. GATs leverage the concept of attention ...
Abstract: Graph Transformers, emerging as a new architecture for graph representation learning, suffer from the quadratic complexity and can only handle graphs with at most thousands of nodes. To this ...
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