Methods › Graphs › Graph Representation Learning › AD-GCL
Adversarial Graph Contrastive Learning
AD-GCL
Introduced by Susheel Suresh et al. in Adversarial Graph Augmentation to Improve Graph Contrastive Learning
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The archive carries no description for this method.
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.
-
On the Adversarial Robustness of Graph Contrastive Learning Methods 29 Nov 2023 · 0 repositories · arXiv:2311.17853
-
Adversarial Graph Augmentation to Improve Graph Contrastive Learning 10 Jun 2021 · 1 repository · arXiv:2106.05819Syntology ran 1 of 1 samples · 0 unverified
Tasks archive 2025-07-28
5 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 |
|---|---|
| Contrastive Learning | 2 |
| Adversarial Robustness | 1 |
| Graph Classification | 1 |
| Node Classification | 1 |
| Self-Supervised Learning | 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