Neural Subgraph Counting with Wasserstein Estimator
Summary: NeurSC: an approximate subgraph counting algorithm with two components: an extraction module and a Wasserstein estimator WEst. It deploys a Wasserstein discriminator to align query and data graphs, enabling robust, scalable estimation on large real graphs. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Hanchen Wang (University of New South Wales; University of Technology Sydney)
- 2. Rong Hu (University of Technology Sydney)
- 3. Ying Zhang (University of Technology Sydney)
- 4. Lu Qin (University of Technology Sydney)
- 5. Wei Wang (Hong Kong University of Science and Technology)
- 6. Wenjie Zhang (University of New South Wales)
BibTeX Citation
@inproceedings{wang_sigmod22,
title = {{Neural Subgraph Counting with Wasserstein Estimator}},
author = {Wang, Hanchen and Hu, Rong and Zhang, Ying and Qin, Lu and Wang, Wei and Zhang, Wenjie},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3526163},
url = {https://dl.acm.org/doi/10.1145/3514221.3526163},
year = {2022}
}
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