Graph convolutional networks (GCN)
Generalization of neural networks to arbitrary graphs.
Relations
relates to Graph isomorphism problem
The graph isomorphism problem is the computational problem of determining whether two finite graphs a...
A graph neural network (GNN) is a class of neural networks for processing data represented by graph d...
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Resources
compared in How Powerful are Graph Neural Networks?
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Despite GNNs revolutionizing graph representation learning, there is limited understanding of their r...
cons given in How powerful are Graph Convolutions? (review of Kipf & Welling, 2016)
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This post is about a paper that has just come out recently on practical generalizations of convolutio...
treated in Graph convolutional networks
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Many important real-world datasets come in the form of graphs or networks: social networks, knowledge...
treated in Geometric Deep Learning
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This website represents a collection of materials in the field of Geometric Deep Learning. We collect...
discussed in A Comprehensive Survey on Graph Neural Networks
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There is an increasing number of applications where data are generated from non-Euclidean domains and...