Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings
Author:
Affiliation:
1. Virginia Tech, Arlington, VA, USA
2. University of Minnesota, Minneapolis, MN, USA
3. University of Buffalo, Buffalo, NY, USA
Funder
National Science Foundation
Amazon AWS credits
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3404835.3462960
Reference36 articles.
1. SimGNN
2. Yunsheng Bai Hao Ding Ken Gu Yizhou Sun and Wei Wang. 2020. Learning-Based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching. In AAAI. 3219--3226. Yunsheng Bai Hao Ding Ken Gu Yizhou Sun and Wei Wang. 2020. Learning-Based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching. In AAAI. 3219--3226.
3. Efficient matching and indexing of graph models in content-based retrieval
4. On a relation between graph edit distance and maximum common subgraph
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