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 301–310 of 1192 papers

TitleStatusHype
FILDNE: A Framework for Incremental Learning of Dynamic Networks EmbeddingsCode0
Learning Combinatorial Optimization Algorithms over GraphsCode0
Graph Embedding based Wireless Link Scheduling with Few Training SamplesCode0
A Simple Baseline Algorithm for Graph ClassificationCode0
Graph-Embedded Subspace Support Vector Data DescriptionCode0
Combining exogenous and endogenous signals with a semi-supervised co-attention network for early detection of COVID-19 fake tweetsCode0
Graph Embedding Augmented Skill Rating SystemCode0
Graph Embedding on Biomedical Networks: Methods, Applications, and EvaluationsCode0
A robust feature reinforcement framework for heterogeneous graphs neural networksCode0
Graph Coordinates and Conventional Neural Networks -- An Alternative for Graph Neural NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified