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Beschreibung
🚀 Heterogeneous Graph Explanation
Explainability support for heterogeneous graphs. There exist simple ways to adapt current explainability methods into heterogeneous graphs. For example, we can use gradient-based methods by taking gradient with respect to adjacencies (edge_index) of different message types. We can also adapt GNNExplainer by creating a mask corresponding to each of the edge_index for different message types.
Thanks for the good points@Padarn and @wsad1! I'll discuss offline and update this issue with more details for things like HGTConv in a few days.
Tasks:
- Extension of the current explainability framework to work for HeteroData objects.
- Incorporate captum-based explainability implementation (such as SHAP, DeepLIFT) for HeteroData.
- Potential extension to hypergraph use cases (where the graph data is represented as nodes and a set of hyperedges which can connect more than 2 nodes).
Alternatives
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Additional context
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