# Graph-Matching-Networks

**Repository Path**: kangleli/Graph-Matching-Networks

## Basic Information

- **Project Name**: Graph-Matching-Networks
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-06-08
- **Last Updated**: 2021-06-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Graph Matching Networks

This is a PyTorch re-implementation of the following ICML 2019 paper. If you feel this project helpful to your research, please give a star.

> Yujia Li, Chenjie Gu, Thomas Dullien, Oriol Vinyals, Pushmeet Kohli. *Graph Matching Networks for Learning the Similarity of Graph Structured Objects*. ICML 2019. [[arXiv\]](https://arxiv.org/abs/1904.12787).

## Requirements

torch >= 1.2.0

networkx>=2.3  

numpy>=1.16.4  

six>=1.12

## Usage

The code includes:

- an example implementation of the model,
- an example graph similarity learning task,
- an example training loop.


Please use `./run.sh` to run.

## References:

[Deepmind-research](https://github.com/deepmind/deepmind-research/tree/master/graph_matching_networks) (using TensorFlow and Sonnet)