Papers › Deep Graph Matching Consensus
Deep Graph Matching Consensus
Matthias Fey, Jan E. Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege
This work presents a two-stage neural architecture for learning and refining structural correspondences between graphs. First, we use localized node embeddings computed by a graph neural network to obtain an initial ranking of soft correspondences between nodes. Secondly, we employ synchronous message passing networks to iteratively re-rank the soft correspondences to reach a matching consensus in local neighborhoods between graphs. We show, theoretically and empirically, that our message passing scheme computes a well-founded measure of consensus for corresponding neighborhoods, which is then used to guide the iterative re-ranking process. Our purely local and sparsity-aware architecture scales well to large, real-world inputs while still being able to recover global correspondences consistently. We demonstrate the practical effectiveness of our method on real-world tasks from the fields of computer vision and entity alignment between knowledge graphs, on which we improve upon the current state-of-the-art. Our source code is available under https://github.com/rusty1s/ deep-graph-matching-consensus.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Entity Alignment | DBP15k zh-en | Deep Graph Matching Consensus (L=10) | Hits@1 | 0.8012 | #12 of 38 | Archive leaderboard | report |
| Entity Alignment | DBP15k zh-en | Deep Graph Matching Consensus | Hits@1 | 0.7075 | #20 of 38 | Archive leaderboard | report |
| Entity Alignment | DBP15k zh-en | GMNN | Hits@1 | 0.6793 | #23 of 38 | Archive leaderboard | report |
| Entity Alignment | DBP15k zh-en | NAEA | Hits@1 | 0.6501 | #24 of 38 | Archive leaderboard | report |
| Entity Alignment | DBP15k zh-en | BootEA | Hits@1 | 0.6294 | #26 of 38 | Archive leaderboard | report |
| Entity Alignment | DBP15k zh-en | MuGNN | Hits@1 | 0.494 | #30 of 38 | Archive leaderboard | report |
| Entity Alignment | DBP15k zh-en | GCN-Align | Hits@1 | 0.4125 | #35 of 38 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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