tkipf/gcn
TensorFlow implementation of Graph Convolutional Networks for semi-supervised node classification in graphs.
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This repository provides a reference implementation of Graph Convolutional Networks (GCN) as described in the 2017 ICLR paper by Kipf and Welling. It implements graph convolution operations using TensorFlow to learn representations of nodes in graph-structured data. The implementation includes both standard GCN and a Chebyshev polynomial version, supporting citation network datasets like Cora, Citeseer, and Pubmed for benchmarking.
Frequently asked
- What is tkipf/gcn?
- TensorFlow implementation of Graph Convolutional Networks for semi-supervised node classification in graphs.
- Is gcn open source?
- Yes — tkipf/gcn is open source, released under the MIT license.
- What language is gcn written in?
- tkipf/gcn is primarily written in Python.
- How popular is gcn?
- tkipf/gcn has 7.4k stars on GitHub.
- Where can I find gcn?
- tkipf/gcn is on GitHub at https://github.com/tkipf/gcn.