# Graph Matching via Optimal Transport

@article{SaadEldin2021GraphMV, title={Graph Matching via Optimal Transport}, author={Ali Saad-Eldin and Benjamin D. Pedigo and Carey E. Priebe and Joshua T. Vogelstein}, journal={ArXiv}, year={2021}, volume={abs/2111.05366} }

The graph matching problem seeks to find an alignment between the nodes of two graphs that minimizes the number of adjacency disagreements. Solving the graph matching is increasingly important due to it’s applications in operations research, computer vision, neuroscience, and more. However, current stateof-the-art algorithms are inefficient in matching very large graphs, though they produce good accuracy. The main computational bottleneck of these algorithms is the linear assignment problem…

## 3 Citations

### Bisected graph matching improves automated pairing of bilaterally homologous neurons from connectomes

- Computer SciencebioRxiv
- 2022

This work presents a modification to a state-of-the-art graph matching algorithm which allows it to solve what they call the bisected graph matching problem and shows that when edge correlation is present between the contralateral (between hemisphere) subgraphs, this approach improves matching accuracy.

### Multiscale Graph Comparison via the Embedded Laplacian Distance

- Computer Science, MathematicsArXiv
- 2022

This work proposes the Embedded Laplacian Distance (ELD), a simple and fast method for comparing graphs of different sizes that is a pseudometric and is invariant under graph isomorphism and provides intuitive interpretations of the ELD using tools from spectral graph theory.

### Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport

- Computer ScienceArXiv
- 2022

This work improves bilingual lexicon induction performance across 32 diverse language pairs with a graph-matching method based on opti- mal transport that is especially strong with very low amounts of supervision.

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