2023
DOI: 10.4018/978-1-6684-6903-3.ch006
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Fundamental Concepts in Graph Attention Networks

R. Soujanya,
Ravi Mohan Sharma,
Manish Manish Maheshwari
et al.

Abstract: Graph attention networks, also known as GATs, are a specific kind of neural network design that can function on input that is arranged as a graph. These networks make use of masked self-attentional layers in order to compensate for the shortcomings that were present in prior approaches that were based on graph convolutions. The main advantage of GAT is its ability to model the dependencies between nodes in a graph, while also allowing for different weights to be assigned to different edges in the graph. GAT is… Show more

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