Jan 9, 2024 · In this work, we propose GNNShap, which provides explanations for edges since they provide more natural explanations for graphs and more fine-grained ...
May 13, 2024 · In this work, we propose GNNShap, which provides explanations for edges since they provide more natural explanations for graphs and more fine-grained ...
We develop GNNShap, a Shapley value based GNN explana- tion model that provides importance scores for all relevant edges for a target node. GNNShap enhanced the ...
Jan 22, 2024 · In this work, we propose GNNShap, which provides explanations for edges since they provide more natural explanations for graphs and more fine-grained ...
This repository contains the source code of GNNShap: Scalable and Accurate GNN Explanation using Shapley Values paper accepted in The Web Conference 2024.
Mar 18, 2024 · "GNNShap: Scalable and Accurate GNN Explanation using Shapley Values Selahattin Akkas, Ariful Azad"
Scalable and Accurate GNN Explanation using Shapley Values
www.researchgate.net › publication › 38...
Oct 6, 2024 · Hence, we extend the GNN classification explainable design, GNNSHAP [25] , modify it to be able to work as a regression explainable design and ...
Feb 15, 2024 · Source code of "GNNShap: Scalable and Accurate GNN Explanation using Shapley Values" Please refer to the README.md file for instructions.
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Co-authors ; GNNShap: Scalable and Accurate GNN Explanation using Shapley Values. S Akkas, A Azad. Proceedings of the ACM on Web Conference 2024, 827-838, 2024.
[01/23/2024] My work “GNNShap: Scalable and Accurate GNN Explanation using Shapley Values” has been accepted as a conference paper at the ACM Web Conference ...