1. Survey

• How Powerful Graph Neural Networks? - GIN :: [ paper_review ]
• A Comprehensive Survey on Graph Neural Networks
• A Comprehensive Survey of Graph Embedding - Problems, Techniques and Applications
• Graph neural networks: A review of methods and applications
• Graph Neural Netwokrs for Recommender Systems : Challenges, Methods, and Directions
• Recipe for a General, Powerful, Scalable Graph Transformer
• Everything is Connected: Graph Neural Networks
• A Survey on Heterogeneous Graph Embedding : Methods, Techniques, Applications and Sources
• Community detection in graphs

2. Aggregate architecture

• DeepWalk - Online Learning of Social Representations :: [ paper_review ]
• node2vec: Scalable Feature Learning for Networks :: [ paper_review ]
• Structural Deep Network Embedding : SDNE :: [ paper review ]
• Structural Deep Clustering Network
• Link prediction for ex ante influence maximization on temporal networks
• MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding
• Semi-Supervised Classification with Graph Convolutional Networks - GCN :: [ paper_review ]
• Adaptive Graph Convolutional Neural Networks - AGCN
• DeepGCNs: Can GCNs Go as Deep as CNNs? - DeepGCN
• GEOM-GCN: Geometric Graph Convolutional networks
• Graph Convolutional Matrix Completion
• GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
• Gated Graph Sequence Neural Networks - GGNN
• Inductive Representation Learning on Large Graphs - GraphSAGE :: [ paper_review ]
• Composition-based multi-relational graph convolutional networks - CompGCN
• Modeling Relational Data with Graph Convolutional Networks - RGCN
• Graph Attention Networks - GAT :: [ paper_review ]
• Heterogeneous Graph Neural Network - HetGNN :: [ paper_review ]
• Heterogeneous graph Attention Network - HAN :: [ paper_review ]
• Hierarchical Graph Pooling with Structure Learning - HGP-SL
• Graph Transformer Networks - GTN
• Heterogeneous Graph Transformer
• Graph Inductive Biases in Transformers without Message Passing
• Do Transformer Really Perform Bad for Graph Representation - Graphormer :: [ paper_review ]
• Watch Your Step: Learning Node Embeddings via Graph Attention
• Universal Graph Transformer Self-Attention Networks
• metapath2vec: Scalable Representation Learning for Heterogeneous Networks :: [ paper_review ]
• Large Graph Property Prediction via Graph Segment Training
• TpuGraphs : A Performance Prediction Dataset on Large Tensor Computational Graphs

3. Graph Pooling

• Graph U-Nets
• Hierarchical Graph Representation Learning with Differentiable Pooling
• Graph Convolutional Networks with EigenPooling
• Self-Attention Graph Pooling
• Hierarchical Graph Capsule Network
• Understanding Attention and Generalization in Graph Neural Networks

4. Temporal Graph Learning

• Graph Deep Learning for Time Series Forecasting :: [ Slides ]
• Using Causality-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs

5. Community Detection

• Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks

6.Knowledge Graph

• Translating Embeddings for Modeling Multi-relational Data
• Learning Entity and Relation Embeddings for Knowledge Graph Completion
• Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models

7. Application

• Graph Convoultional Networks for Text Classification
• Graph-based Neural Multi-Document Summarization
• GNNExplainer : Generating Explanations for Graph Neural Networks :: [ paper_review ]
• GCN-LRP explanation: exploring latent attention of graph convolutional networks
• Graph Convolutional Neural Networks for Web-Scale Recommender Systems - PinSAGE
• Graph Neural Networks for Social Recommendation
• Knowledge Graph Self-Supervised Rationalization for Recommendation
• Graph Convolutional Networks for Hyperspectral Image Classification - miniGCN :: [ paper_review ]
• Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data
• Spatial context-aware method for urban land use classification using street view images :: [ paper_review ]
• A Heterogeneous Graph-based Framework for Scalable Fraud Detection
• Heterogeneous Graph Contrastive Learning for Recommendation
• Incorporating Graph Attention and Recurrent Architectures for City-Wide Taxi Demand Prediction
• TimeGraphs: Graph-based Temporal Reasoning