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 701–710 of 1192 papers

TitleStatusHype
Learning to Borrow– Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion—0
Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network—0
Vertex Nomination, Consistent Estimation, and Adversarial Modification—0
Learning to Map Natural Language Statements into Knowledge Base Representations for Knowledge Base Construction—0
Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems—0
Learn to Unlearn: Meta-Learning-Based Knowledge Graph Embedding Unlearning—0
Leveraging Knowledge Graph Embedding Techniques for Industry 4.0 Use Cases—0
Leveraging Static Models for Link Prediction in Temporal Knowledge Graphs—0
Leveraging Users' Social Network Embeddings for Fake News Detection on Twitter—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