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Graph Convolutional Neural Networks via Scattering
March 31, 2018 Β· Declared Dead Β· π Applied and Computational Harmonic Analysis
"No code URL or promise found in abstract"
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Authors
Dongmian Zou, Gilad Lerman
arXiv ID
1804.00099
Category
cs.IT: Information Theory
Cross-listed
cs.LG,
eess.SP
Citations
127
Venue
Applied and Computational Harmonic Analysis
Last Checked
4 months ago
Abstract
We generalize the scattering transform to graphs and consequently construct a convolutional neural network on graphs. We show that under certain conditions, any feature generated by such a network is approximately invariant to permutations and stable to graph manipulations. Numerical results demonstrate competitive performance on relevant datasets.
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