Methods › Graphs › Graph Models › PinvGCN
Pseudoinverse Graph Convolutional Network
PinvGCN
Introduced by Dominik Alfke et al. in Pseudoinverse Graph Convolutional Networks: Fast Filters Tailored for Large Eigengaps of Dense Graphs and Hypergraphs
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A GCN method targeted at the unique spectral properties of dense graphs and hypergraphs, enabled by efficient numerical linear algebra.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Pseudoinverse Graph Convolutional Networks: Fast Filters Tailored for Large Eigengaps of Dense Graphs and Hypergraphs 3 Aug 2020 · 1 repository · arXiv:2008.00720
Tasks archive 2025-07-28
1 task the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Computational Efficiency | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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