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Adversarial attacks and defenses on Graph Neural Networks.

394
GitHub Stars
75
Curated Resources
4
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23 hours ago
Last Refreshed
1. Survey Papers2. Attack Papers3. Defense Papers4. Certified Robustness Papers

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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:

"Show me 2.2 untargeted attack resources from awesome-graph-attack-papers"

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What's inside

2. Attack Papers

3. Defense Papers

4. Certified Robustness Papers

Showing a sample of 75 resources. View the full list on GitHub →