SOTAVerified

Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

( Image credit: GAT )

Papers

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Showing 1111–1120 of 1192 papers

TitleStatusHype
Improving Knowledge Graph Embedding Using Simple ConstraintsCode0
RECS: Robust Graph Embedding Using Connection Subgraphs—0
Learning to Map Natural Language Statements into Knowledge Base Representations for Knowledge Base Construction—0
Feature Propagation on Graph: A New Perspective to Graph Representation Learning—0
Not all Embeddings are created Equal: Extracting Entity-specific Substructures for RDF Graph Embedding—0
Expeditious Generation of Knowledge Graph EmbeddingsCode0
Billion-scale Commodity Embedding for E-commerce Recommendation in AlibabaCode0
MILE: A Multi-Level Framework for Scalable Graph EmbeddingCode0
A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks—0
The Importance of Norm Regularization in Linear Graph Embedding: Theoretical Analysis and Empirical Demonstration—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified