Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings

Computer Science > Artificial Intelligence [Submitted on 16 Jul 2024 (v1), last revised 2 Jun 2026 (this version, v2)] Title:Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings View PDF HTML (experimental)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. Submission history From: Yuqicheng Zhu [view email][v1] Tue, 16 Jul 2024 15:08:33 UTC (374 KB) [v2] Tue, 2 Jun 2026 15:30:29 UTC (69 KB) References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.