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On January 3, 2025 at 12:07:16 AM UTC, admin:
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Changed value of field
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in Learnt Sparsification for Interpretable Graph Neural Networks -
Changed value of field
doi_date_published
to2025-01-03
in Learnt Sparsification for Interpretable Graph Neural Networks -
Added resource Original Metadata to Learnt Sparsification for Interpretable Graph Neural Networks
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15 | "extra_author": "Zijian Zhang", | 15 | "extra_author": "Zijian Zhang", | ||
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57 | "learnt-sparsi-cation-for-interpretable-graph-neural-networks", | 57 | "learnt-sparsi-cation-for-interpretable-graph-neural-networks", | ||
58 | "notes": "Graph neural networks (GNNs) have achieved great success | 58 | "notes": "Graph neural networks (GNNs) have achieved great success | ||
59 | on various tasks and fields that require relational modeling. GNNs | 59 | on various tasks and fields that require relational modeling. GNNs | ||
60 | aggregate node features using the graph structure as inductive biases | 60 | aggregate node features using the graph structure as inductive biases | ||
61 | resulting in flexible and powerful models. However, GNNs remain hard | 61 | resulting in flexible and powerful models. However, GNNs remain hard | ||
62 | to interpret as the interplay between node features and graph | 62 | to interpret as the interplay between node features and graph | ||
63 | structure is only implicitly learned.", | 63 | structure is only implicitly learned.", | ||
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