Tag: explainability
All the talks with the tag "explainability".
Private Graph Extraction via Feature Explanation
Rishi Raj SahooPublished: at 02:00 PMThis study explores privacy leakage in GNNs through graph reconstruction attacks using feature explanations. It compares explanation methods—gradient-based, perturbation-based, and surrogate model-based—showing that explanations aid graph reconstruction, with a trade-off between privacy and utility. A defense using randomized response is proposed to reduce attack success.
GNNX-BENCH - Perturbation-based GNN Explainers
Rishi Raj SahooPublished: at 02:00 PMThis work presents a benchmark for Graph Neural Network Explainability with perturbation. This involves some metrics like Sufficiency, Necessity, Stability, and Reproducibility to observe which method performs better. Finally, the work provides recommendations for choosing methods for particular graph tasks.