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 911–920 of 1192 papers

TitleStatusHype
An Investigation of Evaluation Metrics for Automated Medical Note GenerationCode0
APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph EmbeddingCode0
A parameter-free graph reduction for spectral clustering and SpectralNetCode0
A Physical Embedding Model for Knowledge GraphsCode0
Approximate spectral clustering density-based similarity for noisy datasetsCode0
Approximate spectral clustering with eigenvector selection and self-tuned kCode0
Arbitrary Time Information Modeling via Polynomial Approximation for Temporal Knowledge Graph EmbeddingCode0
Are Graph Embeddings the Panacea? An Empirical Survey from the Data Fitness PerspectiveCode0
A Robust and Generalized Framework for Adversarial Graph EmbeddingCode0
A robust feature reinforcement framework for heterogeneous graphs neural networksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified