A Regularized Attention Mechanism for Graph Attention Networks
Published: May 1, 2020
Abstract
Machine learning models that can exploit the inherent structure in data have gained prominence. In particular, there is a surge in deep learning solutions for graph-structured data, due to its wide-spread applicability in several fields. Graph attention networks (GAT), a recent addition to the broad class of feature learning models in graphs, utilizes the attention mechanism to efficiently learn continuous vector representations for...
Paper Details
Title
A Regularized Attention Mechanism for Graph Attention Networks
Published Date
May 1, 2020
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