Semantic interpretation and validation of graph attention-based explanations for GNN models
In this work, we propose a methodology for investigating the use of semantic attention to enhance the explainability of Graph Neural Network (GNN)-based models. Graph Deep Learning (GDL) has emerged as a promising field for tasks like scene interpretation, leveraging flexible graph structures to con...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
IEEE
2024
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