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Entity Embeddings

Entity Embeddings is a technique for applying deep learning to tabular data. It involves representing the categorical data of an information systems entity with multiple dimensions.

Papers

Showing 2130 of 151 papers

TitleStatusHype
InGram: Inductive Knowledge Graph Embedding via Relation GraphsCode1
Message Passing Query EmbeddingCode1
Entity-aware Transformers for Entity SearchCode1
Query2Particles: Knowledge Graph Reasoning with Particle EmbeddingsCode1
Complex Temporal Question Answering on Knowledge GraphsCode1
RDF2Vec: RDF Graph Embeddings and Their ApplicationsCode1
AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language ModelsCode1
Meta-Knowledge Transfer for Inductive Knowledge Graph EmbeddingCode1
Contextual Parameter Generation for Knowledge Graph Link PredictionCode1
Improving Entity Linking through Semantic Reinforced Entity EmbeddingsCode1
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