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 161–170 of 1192 papers

TitleStatusHype
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
Contrastive Deep Nonnegative Matrix Factorization for Community DetectionCode1
A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule LearningCode1
CausE: Towards Causal Knowledge Graph EmbeddingCode1
GraphSAINT: Graph Sampling Based Inductive Learning MethodCode1
Hardware-agnostic Computation for Large-scale Knowledge Graph EmbeddingsCode1
Approximating Network Centrality Measures Using Node Embedding and Machine LearningCode1
Expressive Power of Invariant and Equivariant Graph Neural NetworksCode1
How to Turn Your Knowledge Graph Embeddings into Generative ModelsCode1
Graph Neural Networks for Distributed Power Allocation in Wireless Networks: Aggregation Over-the-AirCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified