Jan 17, 2020 · GraphLIME is a generic GNN-model explanation framework that learns a nonlinear interpretable model locally in the subgraph of the node being explained.

Through experiments on two real-world datasets, the explanations of GraphLIME are found to be of extraordinary degree and more descriptive in comparison to the ...

GraphLIME is a generic GNN-model explanation framework that learns a nonlinear interpretable model locally in the subgraph of the node being explained.

GraphLIME is a generic GNN-model explanation framework that learns a nonlinear interpretable model locally in the subgraph of the node being explained. Through ...

GraphLIME is a model-agnostic, local, and nonlinear explanation method for GNN in node classfication task. It uses Hilbert-Schmit Independence Criterion ...

Sep 27, 2020 · ... Local Interpretable Model Explanation for Graph Neural Networks (GraphLIME), which is a nonlinear model-agnostic explanation framework for GNNs.

GraphLIME is a generic GNN-model explanation framework that learns a nonlinear interpretable model locally in the subgraph of the node being explained.

GraphLIME is a generic GNN-model explanation framework that learns a nonlinear interpretable model locally in the subgraph of the node being explained, ...

Graphlime: Local interpretable model explanations for graph neural networks. Huang, Q., Yamada, M., Tian, Y., Singh, D., & Chang, Y. IEEE Transactions on ...

Sep 15, 2023 · Huang, Q., Yamada, M., Tian, Y., Singh, D. and Chang, Y. (2022) Graphlime Local Interpretable Model Explanations for Graph Neural Networks.