Preprint
Robust Counterfactual Explanations on Graph Neural Networks
Abstract
Massive deployment of Graph Neural Networks (GNNs) in high-stake applications
generates a strong demand for explanations that are robust to noise and align
Authors
Bajaj M; Chu L; Xue ZY; Pei J; Wang L; Lam PC-H; Zhang Y
Publication date
July 8, 2021
DOI
10.48550/arxiv.2107.04086
Preprint server
arXiv