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 631–640 of 1192 papers

TitleStatusHype
Scaling Knowledge Graph Embedding Models—0
Stay Positive: Knowledge Graph Embedding Without Negative SamplingCode0
Neighbor2vec: an efficient and effective method for Graph Embedding—0
Sparse-Dyn: Sparse Dynamic Graph Multi-representation Learning via Event-based Sparse Temporal Attention Network—0
Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings—0
Semi-Supervised Graph Attention Networks for Event Representation LearningCode0
CSSR: A Context-Aware Sequential Software Service Recommendation ModelCode0
A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods—0
Manifold learning via quantum dynamics—0
Two-view Graph Neural Networks for Knowledge Graph CompletionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified