Providing Post-Hoc Explanation for Node Representation Learning Models Through Inductive Conformal Predictions
Learning with graph-structured data, such as social, biological, and financial networks, requires effective low-dimensional representations to handle their large and complex interactions. Recently, with the advances of neural networks and embedding algorithms, many unsupervised approaches have been...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10003193/ |