Methods › Graphs › Graph Representation Learning › GFSA
Graph Finite-State Automaton
GFSA
Introduced by Daniel D. Johnson et al. in Learning Graph Structure With A Finite-State Automaton Layer
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Graph Finite-State Automaton, or GFSA, is a differentiable layer for learning graph structure that adds a new edge type (expressed as a weighted adjacency matrix) to a base graph. This layer can be trained end-to-end to add derived relationships (edges) to arbitrary graph-structured data based on performance on a downstream task.
Papers archive 2025-07-28
2 shown of 2, 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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Graph Convolutions Enrich the Self-Attention in Transformers! 7 Dec 2023 · 1 repository · arXiv:2312.04234Syntology ran 19 of 29 samples · 10 unverified
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Learning Graph Structure With A Finite-State Automaton Layer 9 Jul 2020 · 1 repository · arXiv:2007.04929
Tasks archive 2025-07-28
9 tasks 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 |
|---|---|
| Clone Detection | 1 |
| Code Classification | 1 |
| Defect Detection | 1 |
| Graph Regression | 1 |
| Image Classification | 1 |
| Speech Recognition | 1 |
| Time Series | 1 |
| Variable misuse | 1 |
| speech-recognition | 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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections