Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings
📰 ArXiv cs.AI
Learn how knowledge graph embeddings can approximate probabilistic inference in Statistical EL efficiently
Action Steps
- Apply knowledge graph embeddings to Statistical EL to approximate probabilistic inference
- Use the example of Statistical EL to understand the implementation of knowledge graph embeddings
- Evaluate the runtime and approximation quality of the approach using empirical methods
- Configure the knowledge graph embeddings to achieve soundness guarantees
- Test the approach using proofs for runtime and soundness guarantees
Who Needs to Know This
Data scientists and AI researchers working with knowledge graphs and statistical inference can benefit from this approach to improve the efficiency of their models
Key Insight
💡 Knowledge graph embeddings can efficiently approximate probabilistic inference in Statistical EL
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🤖 Approximate probabilistic inference in Statistical EL using knowledge graph embeddings! 📊
Key Takeaways
Learn how knowledge graph embeddings can approximate probabilistic inference in Statistical EL efficiently
Full Article
Title: Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings
Abstract:
arXiv:2407.11821v2 Announce Type: replace Abstract: Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard. We explain how knowledge graph embeddings can be used to approximate probabilistic inference efficiently using the example of Statistical EL (SEL), a statistical extension of the lightweight Description Logic EL. We provide proofs for runtime and soundness guarantees, and empirically evaluate the runtime and approximation quality of our approach.
Abstract:
arXiv:2407.11821v2 Announce Type: replace Abstract: Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard. We explain how knowledge graph embeddings can be used to approximate probabilistic inference efficiently using the example of Statistical EL (SEL), a statistical extension of the lightweight Description Logic EL. We provide proofs for runtime and soundness guarantees, and empirically evaluate the runtime and approximation quality of our approach.
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