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 261–270 of 1192 papers

TitleStatusHype
Curvature Regularization to Prevent Distortion in Graph Embedding—0
CTAGE: Curvature-Based Topology-Aware Graph Embedding for Learning Molecular Representations—0
Attention Regularized Laplace Graph for Domain Adaptation—0
Semantic and Expressive Variation in Image Captions Across Languages—0
CTRL: Continuous-Time Representation Learning on Temporal Heterogeneous Information Network—0
A Translation-Based Knowledge Graph Embedding Preserving Logical Property of Relations—0
AMOSL: Adaptive Modality-wise Structure Learning in Multi-view Graph Neural Networks For Enhanced Unified Representation—0
Adaptive Homophily Clustering: Structure Homophily Graph Learning with Adaptive Filter for Hyperspectral Image—0
AMCAD: Adaptive Mixed-Curvature Representation based Advertisement Retrieval System—0
Explaining Link Predictions in Knowledge Graph Embedding Models with Influential Examples—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified