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 1011–1020 of 1192 papers

TitleStatusHype
Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social ContextsCode0
Representation Learning for Attributed Multiplex Heterogeneous NetworkCode1
Speed-up and multi-view extensions to Subclass Discriminant AnalysisCode0
RelWalk -- A Latent Variable Model Approach to Knowledge Graph Embedding—0
Riemannian TransE: Multi-relational Graph Embedding in Non-Euclidean Space—0
DEEP GEOMETRICAL GRAPH CLASSIFICATION—0
AutoSF: Searching Scoring Functions for Knowledge Graph EmbeddingCode1
Data Poisoning Attack against Knowledge Graph Embedding—0
Quaternion Knowledge Graph EmbeddingsCode0
Graph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified