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Evaluating explainability for graph neural networks
As explanations are increasingly used to understand the behavior of graph neural networks (GNNs), evaluating the quality and reliability of GNN explanations is crucial. However, assessing the quality of GNN explanations is challenging as existing graph datasets have no or unreliable ground-truth exp...
Autores principales: | Agarwal, Chirag, Queen, Owen, Lakkaraju, Himabindu, Zitnik, Marinka |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024712/ https://www.ncbi.nlm.nih.gov/pubmed/36934095 http://dx.doi.org/10.1038/s41597-023-01974-x |
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