benedekrozemberczki/SimGNN
A PyTorch implementation of SimGNN, a neural network approach for fast graph similarity computation using graph neural networks and attention mechanisms.
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This repository provides a PyTorch implementation of the SimGNN paper from WSDM 2019. It combines learnable graph embedding functions with novel attention mechanisms to approximate Graph Edit Distance (GED) efficiently. The approach maps graphs into embedding vectors and uses a tensor network layer to compute similarity scores between graph pairs.
Frequently asked
- What is benedekrozemberczki/SimGNN?
- A PyTorch implementation of SimGNN, a neural network approach for fast graph similarity computation using graph neural networks and attention mechanisms.
- Is SimGNN open source?
- Yes — benedekrozemberczki/SimGNN is open source, released under the GPL-3.0 license.
- What language is SimGNN written in?
- benedekrozemberczki/SimGNN is primarily written in Python.
- How popular is SimGNN?
- benedekrozemberczki/SimGNN has 814 stars on GitHub.
- Where can I find SimGNN?
- benedekrozemberczki/SimGNN is on GitHub at https://github.com/benedekrozemberczki/SimGNN.