A Comprehensive Survey on Graph Neural Networks

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

• Graph neural networks: A review of methods and applications→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
• Knowledge Graphs→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
• DeepGCNs: Can GCNs Go As Deep As CNNs?→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Long Short-Term MemoryLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Transla…Legacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…Legacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→The Graph Neural Network ModelLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→DeepWalkLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Effective Approaches to Attention-based Neural Machine TranslationLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Graph Attention NetworksLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Tr…Legacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Modeling Relational Data with Graph Convolutional NetworksLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→LINELegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Formal Semantics for Kolmogorov-Arnold Network Representations of Operational GamesLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Heterogeneous Graph Attention NetworkLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Graph WaveNet for Deep Spatial-Temporal Graph ModelingLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Structural Deep Network EmbeddingLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Deeper Insights Into Graph Convolutional Networks for Semi-Supervised LearningLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Relational inductive biases, deep learning, and graph networksLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→A Comprehensive Survey of Graph Embedding: Problems, Techniques, and ApplicationsLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Toward an Architecture for Never-Ending Language LearningLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→A new model for learning in graph domainsLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Graph embedding techniques, applications, and performance: A surveyLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic\n ForecastingLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→Identifying Resilient Communities in Road Networks: A Path-Based Embedding ApproachLegacy edge — source detail unavailable
• A Comprehensive Survey on Graph Neural Networks→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
• Spectral Networks and Locally Connected Networks on Graphs→Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…Legacy edge — source detail unavailable
• LINE→DeepWalkLegacy edge — source detail unavailable
• Effective Approaches to Attention-based Neural Machine Translation→Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Transla…Legacy edge — source detail unavailable
• The Graph Neural Network Model→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Transla…→Long Short-Term MemoryLegacy edge — source detail unavailable
• Structural Deep Network Embedding→LINELegacy edge — source detail unavailable
• Structural Deep Network Embedding→DeepWalkLegacy edge — source detail unavailable
• Structural Deep Network Embedding→Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…Legacy edge — source detail unavailable
• Modeling Relational Data with Graph Convolutional Networks→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Graph embedding techniques, applications, and performance: A survey→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
• Graph embedding techniques, applications, and performance: A survey→LINELegacy edge — source detail unavailable
• Graph embedding techniques, applications, and performance: A survey→DeepWalkLegacy edge — source detail unavailable
• Graph embedding techniques, applications, and performance: A survey→Structural Deep Network EmbeddingLegacy edge — source detail unavailable
• Graph embedding techniques, applications, and performance: A survey→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Graph embedding techniques, applications, and performance: A survey→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• Graph embedding techniques, applications, and performance: A survey→Identifying Resilient Communities in Road Networks: A Path-Based Embedding ApproachLegacy edge — source detail unavailable
• An End-to-End Deep Learning Architecture for Graph Classification→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
• An End-to-End Deep Learning Architecture for Graph Classification→The Graph Neural Network ModelLegacy edge — source detail unavailable
• An End-to-End Deep Learning Architecture for Graph Classification→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• An End-to-End Deep Learning Architecture for Graph Classification→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• Relational inductive biases, deep learning, and graph networks→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Relational inductive biases, deep learning, and graph networks→Effective Approaches to Attention-based Neural Machine TranslationLegacy edge — source detail unavailable
• Relational inductive biases, deep learning, and graph networks→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Long Short-Term MemoryLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Transla…Legacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Structural Deep Network EmbeddingLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Modeling Relational Data with Graph Convolutional NetworksLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Graph embedding techniques, applications, and performance: A surveyLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Relational inductive biases, deep learning, and graph networksLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Heterogeneous Graph Attention NetworkLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Formal Semantics for Kolmogorov-Arnold Network Representations of Operational GamesLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→A Comprehensive Survey of Graph Embedding: Problems, Techniques, and ApplicationsLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic\n ForecastingLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Deeper Insights Into Graph Convolutional Networks for Semi-Supervised LearningLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Graph convolutional networks: a comprehensive reviewLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→LINELegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→DeepWalkLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→Structural Deep Network EmbeddingLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→Modeling Relational Data with Graph Convolutional NetworksLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→LINELegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→Long Short-Term MemoryLegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→The Graph Neural Network ModelLegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→DeepWalkLegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→Structural Deep Network EmbeddingLegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→Graph embedding techniques, applications, and performance: A surveyLegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
• Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning→DeepWalkLegacy edge — source detail unavailable
• Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling→Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic\n ForecastingLegacy edge — source detail unavailable
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling→Graph Attention NetworksLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→DeepWalkLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→Graph embedding techniques, applications, and performance: A surveyLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→Graph Neural Networks: A Review of Methods and ApplicationsLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→A Comprehensive Survey of Graph Embedding: Problems, Techniques, and ApplicationsLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic\n ForecastingLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→Deeper Insights Into Graph Convolutional Networks for Semi-Supervised LearningLegacy edge — source detail unavailable
• DeepGCNs: Can GCNs Go As Deep As CNNs?→Graph Neural Networks: A Review of Methods and ApplicationsLegacy edge — source detail unavailable
• DeepGCNs: Can GCNs Go As Deep As CNNs?→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• DeepGCNs: Can GCNs Go As Deep As CNNs?→Deeper Insights Into Graph Convolutional Networks for Semi-Supervised LearningLegacy edge — source detail unavailable
• DeepGCNs: Can GCNs Go As Deep As CNNs?→Graph Attention NetworksLegacy edge — source detail unavailable
• Knowledge Graphs→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
• Knowledge Graphs→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Knowledge Graphs→Heterogeneous Graph Attention NetworkLegacy edge — source detail unavailable
• Knowledge Graphs→Formal Semantics for Kolmogorov-Arnold Network Representations of Operational GamesLegacy edge — source detail unavailable
• Knowledge Graphs→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Long Short-Term MemoryLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Transla…Legacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Modeling Relational Data with Graph Convolutional NetworksLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Graph embedding techniques, applications, and performance: A surveyLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Relational inductive biases, deep learning, and graph networksLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Heterogeneous Graph Attention NetworkLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Formal Semantics for Kolmogorov-Arnold Network Representations of Operational GamesLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→A Comprehensive Survey of Graph Embedding: Problems, Techniques, and ApplicationsLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic\n ForecastingLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Deeper Insights Into Graph Convolutional Networks for Semi-Supervised LearningLegacy edge — source detail unavailable
• Graph neural networks: A review of methods and applications→Graph convolutional networks: a comprehensive reviewLegacy edge — source detail unavailable