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Graph embedding techniques, applications, and performance: A survey

Knowledge-based systems, 2018-07, Vol.151, p.78-94

2018

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dyngraph2vec: Capturing network dynamics using dynamic graph representation learning

Knowledge-based systems, 2020-01, Vol.187, p.104816, Article 104816

2020

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A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications

IEEE transactions on knowledge and data engineering, 2018-09, Vol.30 (9), p.1616-1637

2018

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A Survey on Embedding Dynamic Graphs

ACM computing surveys, 2023-01, Vol.55 (1), p.1-37

2023

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Dynamic Heterogeneous Graph Embedding Using Hierarchical Attentions

Advances in Information Retrieval, 2020, p.425-432

2020

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DynHEN: A heterogeneous network model for dynamic bipartite graph representation learning

Neurocomputing (Amsterdam), 2022-10, Vol.508, p.47-57, Article 47

2022

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EARR: Using rules to enhance the embedding of knowledge graph

Expert systems with applications, 2023-12, Vol.232, p.120831, Article 120831

2023

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A survey on temporal knowledge graph embedding: Models and applications

Knowledge-based systems, 2024-11, Vol.304, p.112454, Article 112454

2024

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Correntropy-Induced Wasserstein GCN: Learning Graph Embedding via Domain Adaptation

IEEE transactions on image processing, 2023-01, Vol.32, p.1-1

2023

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Adaptive Reference-Related Graph Embedding for Hyperspectral Anomaly Detection

IEEE transactions on geoscience and remote sensing, 2023-01, Vol.61, p.1-1

2023

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A Semi-supervised Matrixized Graph Embedding Machine for Roller Bearing Fault Diagnosis Under Few-labeled Samples

IEEE transactions on industrial informatics, 2024-01, Vol.20 (1), p.1-9

2024

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Improving static and temporal knowledge graph embedding using affine transformations of entities

Web semantics, 2024-10, Vol.82, p.100824, Article 100824

2024

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A Scalable Unsupervised Feature Selection with Orthogonal Graph Representation for Hyperspectral Images

IEEE transactions on geoscience and remote sensing, 2023-01, Vol.61, p.1-1

2023

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Simultaneous Sparse Graph Embedding for Hyperspectral Image Classification

IEEE transactions on geoscience and remote sensing, 2015-11, Vol.53 (11), p.6114-6133

2015

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A Graph Embedding Technique for Weighted Graphs Based on LSTM Autoencoders

Journal of information processing systems, 2020-12, Vol.16 (6), p.1407-1423

2020

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Object Recognition as Many-to-Many Feature Matching

International journal of computer vision, 2006-08, Vol.69 (2), p.203-222

2006

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Geometry-Aware Graph Embedding Projection Metric Learning for Image Set Classification

IEEE transactions on cognitive and developmental systems, 2022-09, Vol.14 (3), p.957-970

2022

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A Graph Embedding Technique for Weighted Graphs Based on LSTM Autoencoders

JIPS(Journal of Information Processing Systems), 2020, 16(6), 66, pp.1407-1423

2020

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ProbWalk: A random walk approach in weighted graph embedding

Procedia computer science, 2021, Vol.183, p.683-689

2021

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GRAFICS: Graph Embedding-based Floor Identification Using Crowdsourced RF Signals

2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS), 2022, p.1051-1061

2022

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Graph Representations for Reinforcement Learning

Journal of computer science and technology (La Plata), 2024-04, Vol.24 (1), p.e03

2024

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GEMimp: An accurate and robust imputation method for microbiome data using graph embedding neural network

Journal of molecular biology, 2024-10, p.168841, Article 168841

2024

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Position-aware and structure embedding networks for deep graph matching

Pattern recognition, 2023-04, Vol.136, p.109242, Article 109242

2023

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Rule-enhanced iterative complementation for knowledge graph reasoning

Information sciences, 2021-10, Vol.575, p.66-79

2021

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Recognizing Weak Embeddings of Graphs

ACM transactions on algorithms, 2019-10, Vol.15 (4), p.1-27

2019

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Graph embedding techniques, applications, and performance: A survey

dyngraph2vec: Capturing network dynamics using dynamic graph representation learning

A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications

A Survey on Embedding Dynamic Graphs

Dynamic Heterogeneous Graph Embedding Using Hierarchical Attentions

DynHEN: A heterogeneous network model for dynamic bipartite graph representation learning

EARR: Using rules to enhance the embedding of knowledge graph

A survey on temporal knowledge graph embedding: Models and applications

Correntropy-Induced Wasserstein GCN: Learning Graph Embedding via Domain Adaptation

Adaptive Reference-Related Graph Embedding for Hyperspectral Anomaly Detection

A Semi-supervised Matrixized Graph Embedding Machine for Roller Bearing Fault Diagnosis Under Few-labeled Samples

Improving static and temporal knowledge graph embedding using affine transformations of entities

A Scalable Unsupervised Feature Selection with Orthogonal Graph Representation for Hyperspectral Images

Simultaneous Sparse Graph Embedding for Hyperspectral Image Classification

A Graph Embedding Technique for Weighted Graphs Based on LSTM Autoencoders

Object Recognition as Many-to-Many Feature Matching

Geometry-Aware Graph Embedding Projection Metric Learning for Image Set Classification

A Graph Embedding Technique for Weighted Graphs Based on LSTM Autoencoders

ProbWalk: A random walk approach in weighted graph embedding

GRAFICS: Graph Embedding-based Floor Identification Using Crowdsourced RF Signals

Graph Representations for Reinforcement Learning

GEMimp: An accurate and robust imputation method for microbiome data using graph embedding neural network

Position-aware and structure embedding networks for deep graph matching

Rule-enhanced iterative complementation for knowledge graph reasoning

Recognizing Weak Embeddings of Graphs

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