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 1041–1050 of 1192 papers

TitleStatusHype
Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation LearningCode0
GraphZoom: A multi-level spectral approach for accurate and scalable graph embeddingCode0
GSIFN: A Graph-Structured and Interlaced-Masked Multimodal Transformer-based Fusion Network for Multimodal Sentiment AnalysisCode0
HetReGAT-FC: heterogeneous residual graph attention network via feature completionCode0
HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk PredictionCode0
Hierarchical Aggregations for High-Dimensional Multiplex Graph EmbeddingCode0
Hierarchical Latent Relation Modeling for Collaborative Metric LearningCode0
Hierarchical stochastic graphlet embedding for graph-based pattern recognitionCode0
HopfE: Knowledge Graph Representation Learning using Inverse Hopf FibrationsCode0
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified