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 51–60 of 1192 papers

TitleStatusHype
Learn to Unlearn: Meta-Learning-Based Knowledge Graph Embedding Unlearning—0
Local Intrinsic Dimensionality for Dynamic Graph Embeddings—0
Domain and Range Aware Synthetic Negatives Generation for Knowledge Graph Embedding Models—0
Visualization of Knowledge Graphs with Embeddings: an Essay on Recent Trends and Methods—0
Scalable Deep Metric Learning on Attributed Graphs—0
Multi-Hyperbolic Space-based Heterogeneous Graph Attention Network—0
Class Granularity: How richly does your knowledge graph represent the real world?—0
Fully Hyperbolic Rotation for Knowledge Graph EmbeddingCode0
JPEC: A Novel Graph Neural Network for Competitor Retrieval in Financial Knowledge Graphs—0
Detecting text level intellectual influence with knowledge graph embeddings—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified