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 731–740 of 1192 papers

TitleStatusHype
Scalable Deep Metric Learning on Attributed Graphs—0
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding—0
Scalable Graph Embedding LearningOn A Single GPU—0
Scalable Graph Embeddings via Sparse Transpose Proximities—0
Scalable Hierarchical Embeddings of Complex Networks—0
Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks—0
A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications—0
Scalar Coupling Constant Prediction Using Graph Embedding Local Attention Encoder—0
Scaling Knowledge Graph Embedding Models—0
SceneSketcher: Fine-Grained Image Retrieval with Scene Sketches—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified