SOTAVerified

Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

( Image credit: GAT )

Papers

Showing 461470 of 1192 papers

TitleStatusHype
Hierarchical stochastic graphlet embedding for graph-based pattern recognitionCode0
Benchmarks for Graph Embedding EvaluationCode0
Hierarchical Aggregations for High-Dimensional Multiplex Graph EmbeddingCode0
An FEA surrogate model with Boundary Oriented Graph Embedding approachCode0
HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk PredictionCode0
Hierarchical Latent Relation Modeling for Collaborative Metric LearningCode0
GSIFN: A Graph-Structured and Interlaced-Masked Multimodal Transformer-based Fusion Network for Multimodal Sentiment AnalysisCode0
GraphZoom: A multi-level spectral approach for accurate and scalable graph embeddingCode0
AttPool: Towards Hierarchical Feature Representation in Graph Convolutional Networks via Attention MechanismCode0
GraphVAE: Towards Generation of Small Graphs Using Variational AutoencodersCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0Unverified