GRB (Graph Robustness Benchmark)
Introduced by Zheng et al. in Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning
Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evaluation on the adversarial robustness of graph machine learning models. GRB has elaborated datasets, unified evaluation pipeline, modular coding framework, and reproducible leaderboards, which facilitate the developments of graph adversarial learning, summarizing existing progress and generating insights into future research.
GitHub: https://github.com/thudm/grb
Papers
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