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  journal   = {Pattern Recognition},
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  doi       = {10.1016/j.patcog.2014.07.015},
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@inproceedings{bfs2018,
  author    = {Jiaxuan You and
               Rex Ying and
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               William L. Hamilton and
               Jure Leskovec},
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  booktitle = {Proceedings of the 35th International Conference on Machine Learning,
               {ICML} 2018, Stockholmsm{\"{a}}ssan, Stockholm, Sweden, July
               10-15, 2018},
  pages     = {5694--5703},
  year      = {2018},
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@inproceedings{canonical2016,
  author    = {Mathias Niepert and
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               Konstantin Kutzkov},
  title     = {Learning Convolutional Neural Networks for Graphs},
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               {ICML} 2016, New York City, NY, USA, June 19-24, 2016},
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  author    = {Pau Riba and
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  booktitle = {24th International Conference on Pattern Recognition, {ICPR} 2018,
               Beijing, China, August 20-24, 2018},
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  year      = {2018},
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@inproceedings{bai2019,
  author    = {Yunsheng Bai and
               Hao Ding and
               Song Bian and
               Ting Chen and
               Yizhou Sun and
               Wei Wang},
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  booktitle = {Proceedings of the Twelfth {ACM} International Conference on Web Search
               and Data Mining, {WSDM} 2019, Melbourne, VIC, Australia, February
               11-15, 2019},
  pages     = {384--392},
  year      = {2019},
  doi       = {10.1145/3289600.3290967},
  timestamp = {Tue, 21 May 2019 11:38:33 +0200},
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  author    = {Yunsheng Bai and
               Hao Ding and
               Yizhou Sun and
               Wei Wang},
  title     = {Convolutional Set Matching for Graph Similarity},
  journal   = {CoRR},
  volume    = {abs/1810.10866},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.10866},
  archivePrefix = {arXiv},
  eprint    = {1810.10866},
  timestamp = {Wed, 31 Oct 2018 14:24:29 +0100},
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  bibsource = {dblp computer science bibliography, https://dblp.org}
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@article{bai2018_cnn2,
  author    = {Yunsheng Bai and
               Hao Ding and
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               Distance},
  journal   = {CoRR},
  volume    = {abs/1809.04440},
  year      = {2018},
  url       = {http://arxiv.org/abs/1809.04440},
  archivePrefix = {arXiv},
  eprint    = {1809.04440},
  timestamp = {Fri, 05 Oct 2018 11:34:52 +0200},
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  author    = {Yujia Li and
               Chenjie Gu and
               Thomas Dullien and
               Oriol Vinyals and
               Pushmeet Kohli},
  title     = {Graph Matching Networks for Learning the Similarity of Graph Structured
               Objects},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning,
               {ICML} 2019, 9-15 June 2019, Long Beach, California, {USA}},
  pages     = {3835--3845},
  year      = {2019},
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  biburl    = {https://dblp.org/rec/conf/icml/LiGDVK19.bib},
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@article{fey2020_update,
  author    = {Matthias Fey and
               Jan Eric Lenssen and
               Christopher Morris and
               Jonathan Masci and
               Nils M. Kriege},
  title     = {Deep Graph Matching Consensus},
  journal   = {CoRR},
  volume    = {abs/2001.09621},
  year      = {2020},
  url       = {https://arxiv.org/abs/2001.09621},
  archivePrefix = {arXiv},
  eprint    = {2001.09621},
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@inproceedings{spline2018,
  author    = {Matthias Fey and
               Jan Eric Lenssen and
               Frank Weichert and
               Heinrich M{\"{u}}ller},
  title     = {SplineCNN: Fast Geometric Deep Learning With Continuous B-Spline Kernels},
  booktitle = {2018 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2018, Salt Lake City, UT, USA, June 18-22, 2018},
  pages     = {869--877},
  year      = {2018},
  doi       = {10.1109/CVPR.2018.00097},
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@inproceedings{pytorchgeometric,
  title={Fast Graph Representation Learning with {PyTorch Geometric}},
  author={Fey, Matthias and Lenssen, Jan E.},
  booktitle={ICLR Workshop on Representation Learning on Graphs and Manifolds},
  year={2019},
}

@article{wang2019,
  author    = {Runzhong Wang and
               Junchi Yan and
               Xiaokang Yang},
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  journal   = {CoRR},
  volume    = {abs/1904.00597},
  year      = {2019},
  url       = {http://arxiv.org/abs/1904.00597},
  archivePrefix = {arXiv},
  eprint    = {1904.00597},
  timestamp = {Wed, 24 Apr 2019 12:21:25 +0200},
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  author    = {Mark Everingham and
               Luc Van Gool and
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               John M. Winn and
               Andrew Zisserman},
  title     = {The Pascal Visual Object Classes {(VOC)} Challenge},
  journal   = {International Journal of Computer Vision},
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  number    = {2},
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  author    = {Lubomir D. Bourdev and
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               Kyoto, Japan, September 27 - October 4, 2009},
  pages     = {1365--1372},
  year      = {2009},
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@inproceedings{zhang2019,
  author    = {Zhen Zhang and
               Wee Sun Lee},
  title     = {Deep Graphical Feature Learning for the Feature Matching Problem},
  booktitle = {2019 {IEEE/CVF} International Conference on Computer Vision, {ICCV}
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  pages     = {5086--5095},
  year      = {2019},
  doi       = {10.1109/ICCV.2019.00519},
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@inproceedings{fingerprint2005,
  author    = {Michel Neuhaus and
               Horst Bunke},
  title     = {A Graph Matching Based Approach to Fingerprint Classification Using Directional Variance},
  booktitle = {Audio- and Video-Based Biometric Person Authentication
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  pages     = {191--200},
  year      = {2005},
}

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  year      = {2019},
  url       = {http://arxiv.org/abs/1907.03199},
  archivePrefix = {arXiv},
  eprint    = {1907.03199},
  timestamp = {Wed, 17 Jul 2019 10:27:36 +0200},
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  author    = {Kristian Birchall and
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  booktitle = {Journal of Chemical Information and Modeling, {J. Chem. Inf. Model.} 2006},
  pages     = {577--586},
  year      = {2006},
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  pages     = {460--467},
  year      = {2009},
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@inproceedings{nytrom2019,
  author    = {Jason Altschuler and
               Francis Bach and
               Alessandro Rudi and
               Jonathan Niles{-}Weed},
  title     = {Massively scalable Sinkhorn distances via the Nystr{\"{o}}m method},
  booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference
               on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14
               December 2019, Vancouver, BC, Canada},
  pages     = {4429--4439},
  year      = {2019},
  timestamp = {Mon, 13 Jan 2020 09:28:31 +0100},
  biburl    = {https://dblp.org/rec/conf/nips/AltschulerBRN19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
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@article{multiscale2016,
  author    = {Bernhard Schmitzer},
  title     = {A Sparse Multiscale Algorithm for Dense Optimal Transport},
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  number    = {2},
  pages     = {238--259},
  year      = {2016},
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  timestamp = {Fri, 26 May 2017 22:54:55 +0200},
  biburl    = {https://dblp.org/rec/journals/jmiv/Schmitzer16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
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@inproceedings{yeast2019,
  author    = {Hongteng Xu and
               Dixin Luo and
               Lawrence Carin},
  title     = {Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching},
  booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference
               on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14
               December 2019, Vancouver, BC, Canada},
  pages     = {3046--3056},
  year      = {2019},
  timestamp = {Fri, 06 Mar 2020 16:59:09 +0100},
  biburl    = {https://dblp.org/rec/conf/nips/XuLC19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
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@inproceedings{pytorch,
  author    = {Adam Paszke and
               Sam Gross and
               Francisco Massa and
               Adam Lerer and
               James Bradbury and
               Gregory Chanan and
               Trevor Killeen and
               Zeming Lin and
               Natalia Gimelshein and
               Luca Antiga and
               Alban Desmaison and
               Andreas K{\"{o}}pf and
               Edward Yang and
               Zachary DeVito and
               Martin Raison and
               Alykhan Tejani and
               Sasank Chilamkurthy and
               Benoit Steiner and
               Lu Fang and
               Junjie Bai and
               Soumith Chintala},
  title     = {PyTorch: An Imperative Style, High-Performance Deep Learning Library},
  booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference
               on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14
               December 2019, Vancouver, BC, Canada},
  pages     = {8024--8035},
  year      = {2019},
  timestamp = {Fri, 06 Mar 2020 16:59:09 +0100},
  biburl    = {https://dblp.org/rec/conf/nips/PaszkeGMLBCKLGA19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{gin2019,
  author    = {Keyulu Xu and
               Weihua Hu and
               Jure Leskovec and
               Stefanie Jegelka},
  title     = {How Powerful are Graph Neural Networks?},
  booktitle = {7th International Conference on Learning Representations, {ICLR} 2019,
               New Orleans, LA, USA, May 6-9, 2019},
  year      = {2019},
  timestamp = {Thu, 25 Jul 2019 13:03:15 +0200},
  biburl    = {https://dblp.org/rec/conf/iclr/XuHLJ19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}