Graph Neural Networks: A Review of Methods and Applications

Citation edge evidence

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

• A review of uncertainty quantification in deep learning: Techniques, applications and cha…→Graph Neural Networks: A Review of Methods and ApplicationsLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→Graph Neural Networks: A Review of Methods and ApplicationsLegacy edge — source detail unavailable
• A survey on deep learning and its applications→Graph Neural Networks: A Review of Methods and ApplicationsLegacy 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
• 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→BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Reinforcement Learning: An IntroductionLegacy 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→Efficient Estimation of Word Representations in Vector SpaceLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→A Wavelet Tour of Signal ProcessingLegacy 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→The Graph Neural Network ModelLegacy 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→Translating Embeddings for Modeling Multi-relational DataLegacy 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→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 on Graph Neural 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→Structural Deep Network EmbeddingLegacy 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→Relational inductive biases, deep learning, and graph networksLegacy 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→Graph Convolutional Networks for Text ClassificationLegacy 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→PathSimLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Graph convolutional networks: a comprehensive reviewLegacy 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→Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic\n ForecastingLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Hypergraph Neural NetworksLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Reasoning With Neural Tensor Networks for Knowledge Base CompletionLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Deep Learning on Graphs: A SurveyLegacy edge — source detail unavailable
• Graph Neural Networks: A Review of Methods and Applications→Heterogeneous Graph Neural NetworkLegacy 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
• 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
• Modeling Relational Data with Graph Convolutional Networks→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Modeling Relational Data with Graph Convolutional Networks→Reasoning With Neural Tensor Networks for Knowledge Base CompletionLegacy edge — source detail unavailable
• Modeling Relational Data with Graph Convolutional Networks→Translating Embeddings for Modeling Multi-relational DataLegacy 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
• An End-to-End Deep Learning Architecture for Graph Classification→Efficient Estimation of Word Representations in Vector SpaceLegacy 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→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Relational inductive biases, deep learning, and graph networks→Translating Embeddings for Modeling Multi-relational DataLegacy edge — source detail unavailable
• Hypergraph Neural Networks→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Hypergraph Neural Networks→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Hypergraph Neural Networks→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→PathSimLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Heterogeneous Graph Attention Network→The Graph Neural Network ModelLegacy 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
• Graph Convolutional Networks for Text Classification→Relational inductive biases, deep learning, and graph networksLegacy edge — source detail unavailable
• Graph Convolutional Networks for Text Classification→A Comprehensive Survey of Graph Embedding: Problems, Techniques, and ApplicationsLegacy edge — source detail unavailable
• Graph Convolutional Networks for Text Classification→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• Graph Convolutional Networks for Text Classification→Deeper Insights Into Graph Convolutional Networks for Semi-Supervised LearningLegacy edge — source detail unavailable
• Graph Convolutional Networks for Text Classification→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→Efficient Estimation of Word Representations in Vector SpaceLegacy 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→Reasoning With Neural Tensor Networks for Knowledge Base CompletionLegacy edge — source detail unavailable
• A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications→Translating Embeddings for Modeling Multi-relational DataLegacy 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→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'…→Efficient Estimation of Word Representations in Vector SpaceLegacy 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
• Heterogeneous Graph Neural Network→PathSimLegacy edge — source detail unavailable
• Heterogeneous Graph Neural Network→Long Short-Term MemoryLegacy edge — source detail unavailable
• Heterogeneous Graph Neural Network→Modeling Relational Data with Graph Convolutional 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→Graph embedding techniques, applications, and performance: A surveyLegacy edge — source detail unavailable
• Graph convolutional networks: a comprehensive review→Graph Convolutional Networks for Text ClassificationLegacy 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
• Graph convolutional networks: a comprehensive review→A Comprehensive Survey on Graph Neural NetworksLegacy 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?→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→A new model for learning in graph domainsLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Long Short-Term MemoryLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→The Graph Neural Network ModelLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Transla…Legacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Structural Deep Network EmbeddingLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Modeling Relational Data with Graph Convolutional NetworksLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Relational inductive biases, deep learning, and graph networksLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Heterogeneous Graph Attention NetworkLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Deeper Insights Into Graph Convolutional Networks for Semi-Supervised LearningLegacy edge — source detail unavailable
• Deep Learning on Graphs: A Survey→Graph convolutional networks: a comprehensive reviewLegacy edge — source detail unavailable
• A survey on deep learning and its applications→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
• A survey on deep learning and its applications→Deep Learning on Graphs: A SurveyLegacy 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→Long Short-Term MemoryLegacy 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→Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Transla…Legacy 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→Modeling Relational Data with Graph Convolutional NetworksLegacy 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→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy 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→Heterogeneous Graph Attention NetworkLegacy 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→A Comprehensive Survey of Graph Embedding: Problems, Techniques, and ApplicationsLegacy 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→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy 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→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable