Construct · 1 fields · 1 citations

graph convolutional network: a standalone construct

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Machine learning

a neural network layer that updates each node from a normalized average of its neighbors' features, derived as a first-order approximation of spectral graph convolutions.

In machine learning, graph convolutional network refers to a neural network layer that updates each node from a normalized average of its neighbors' features, derived as a first-order approximation of spectral graph convolutions. This meaning comes from Kipf (2016) in arXiv.[1]

Unit
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layer3 fields · 5 citationsjingle · one word, three constructs learning6 fields · 14 citationsjingle · one name, six constructs network4 fields · 6 citationsjingle · one word, four constructs

References

Kipf, T. N., & Welling, M. (2016). Semi-Supervised Classification with Graph Convolutional Networks. arXiv. https://doi.org/10.48550/arxiv.1609.02907

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