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 831–840 of 1192 papers

TitleStatusHype
Transductive Data Augmentation with Relational Path Rule Mining for Knowledge Graph Embedding—0
Transformer-Based Multimodal Knowledge Graph Completion with Link-Aware Contexts—0
Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method—0
TransG : A Generative Mixture Model for Knowledge Graph Embedding—0
TransG : A Generative Model for Knowledge Graph Embedding—0
Transition-based Knowledge Graph Embedding with Relational Mapping Properties—0
Translating Embeddings in Document for Modeling Multi-relational Graphs—0
TranS: Transition-based Knowledge Graph Embedding with Synthetic Relation Representation—0
TR at SemEval-2020 Task 4: Exploring the Limits of Language-model-based Common Sense Validation—0
Disentangling Interpretable Generative Parameters of Random and Real-World Graphs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified