Faithful rule extraction for differentiable rule learning models
There is increasing interest in methods for extracting interpretable rules from ML models trained to solve a wide range of tasks over knowledge graphs (KGs), such as KG completion, node classification, question answering and recommendation. Many such approaches, however, lack formal guarantees estab...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
OpenReview
2024
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