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 511–520 of 1192 papers

TitleStatusHype
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
A Multi-purposed Unsupervised Framework for Comparing Embeddings of Undirected and Directed GraphsCode1
AirObject: A Temporally Evolving Graph Embedding for Object IdentificationCode1
Graph Embedding via High Dimensional Model Representation for Hyperspectral Images—0
MDistMult: A Multiple Scoring Functions Model for Link Prediction on Antiviral Drugs Knowledge Graph—0
WalkingTime: Dynamic Graph Embedding Using Temporal-Topological Flows—0
Vulcan: Solving the Steiner Tree Problem with Graph Neural Networks and Deep Reinforcement Learning—0
ReadE: Learning Relation-Dependent Entity Representation for Knowledge Graph Completion—0
Translating Embeddings in Document for Modeling Multi-relational Graphs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified