Attention-based Graph Neural Network for Semi-supervised Learning
arXiv: Machine Learning, Volume abs/1803.03735, 2018.
Recently popularized graph neural networks achieve the state-of-the-art accuracy on a number of standard benchmark datasets for graph-based semi-supervised learning, improving significantly over existing approaches. These architectures alternate between a propagation layer that aggregates the hidden states of the local neighborhood and a ...More
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