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Code accompanying the AAAI 2022 paper "fGOT: Graph Distances based on Filters and Optimal Transport"

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fGOT

This is the code accompanying the AAAI 2022 paper "fGOT: Graph Distances based on Filters and Optimal Transport".

The main algorithms are contained in files fgot_mgd.py and fgot_stochastic_mgd.py. An example on using the algorithms can be found in the jupyter notebook speed_alignment_test.

Some of the files in this code have been taken from the Python OT library (https://github.com/PythonOT/POT).


fGOT paper link: https://ojs.aaai.org/index.php/AAAI/article/view/20738

If you find this code useful in your research, please cite:

@inproceedings{maretic2022fgot,
  title={FGOT: Graph distances based on filters and optimal transport},
  author={Maretic, Hermina Petric and El Gheche, Mireille and Chierchia, Giovanni and Frossard, Pascal},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={36},
  number={7},
  pages={7710--7718},
  year={2022}
}

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Code accompanying the AAAI 2022 paper "fGOT: Graph Distances based on Filters and Optimal Transport"

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