Pretrained model summary

• pure graph embedding

• graph neural network

• graph pretrained model

---

pure graph embedding

title	paper link	code link
DeepWalk: Online Learning of Social Representations	[paper]	[code(python)]
LINE: Large-scale Information Network Embedding	[paper]	[code(c++)]
Watch Your Step: Learning Node Embeddings via Graph Attention	[paper]	[code(python)]
node2vec: Scalable Feature Learning for Networks	[paper]	[code(python)]
Deep Graph Infomax	[paper]	[code(python)]
graph2vec: Learning Distributed Representations of Graphs	[paper]	[code(python)]
struc2vec: Learning Node Representations from Structural Identity	[paper]	[code(python)]
Learning Structural Node Embeddings via Diffusion Wavelets	[paper]	[code(python)]
Label Informed Attributed Network Embedding	[paper]	[code(matlab)]
Accelerated Attributed Network Embedding	[paper]	[code(matlab)][code(python)]
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking	[paper]	[code(python)]
Network Representation Learning with Rich Text Information	[paper]	[code(matlab)]
Structural Deep Network Embedding	[paper]	[code(python)]

---

graph neural network

title	paper link	code link
Diffusion-Convolutional Neural Networks	[paper]	[code(theano)]
Learning Convolutional Neural Networks for Graphs	[paper]	[code(keras)]
Geometric Deep Learning: Going beyond Euclidean data	[paper]	[code]
Deriving Neural Architectures from Sequence and Graph Kernels	[paper]	[code(tensorflow)]
Semi-Supervised Classification with Graph Convolutional Networks	[paper]	[code(pytorch)][code(tensorflow)]
Neural Message Passing for Quantum Chemistry	[paper]	[code(pytorch)]
GRAPH ATTENTION NETWORKS	[paper]	[code(tensorflow)]
Stochastic Training of Graph Convolutional Networks with Variance Reduction	[paper]	[code(tensorflow)]
Link Prediction Based on Graph Neural Networks	[paper]	[code(pytorch)]
HOW POWERFUL ARE GRAPH NEURAL NETWORKS?	[paper]	[code(pytorch)]
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning	[paper]	[code(tensorflow)]
Supervised Community Detection with Line Graph Neural Networks	[paper]	[code(pytorch)]
SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization	[paper]	[code]
An End-to-End Deep Learning Architecture for Graph Classification	[paper]	[code(pytorch)]
Neural Message Passing for Quantum Chemistr	[paper]	[code(pytorch)]
Capsule Graph Neural Network	[paper]	[code(tensorflow)]
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling	[paper]	[code(tensorflow)]
Relational Inductive Biases, Deep Learning, and Graph Networks	[paper]	[code(tensorflow)]
CANE: Context-Aware Network Embedding for Relation Modeling	[paper]	[code(tensorflow)]
DIRECT MULTI-HOP ATTENTION BASED GRAPH NEURAL NETWORKS	[paper]	[code]
DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting	[paper]	[code(pytorch)]
PYTORCH-BIGGRAPH: A LARGE-SCALE GRAPH EMBEDDING SYSTEM	[paper]	[code(pytorch)]
Graph Neural Networks with Convolutional ARMA Filters	[paper]	[code]
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks	[paper]	[code(pytorch)]
Simplifying Graph Convolutional Networks	[paper]	[code(pytorch)]
Graph U-Net	[paper]	[code(pytorch)]
Combining Neural Networks with Personalized PageRank for Classification on Graphs	[paper]	[code(pytorch)]
Modeling Relational Data with Graph Convolutional Networks	[paper]	[code(keras)]
Attention-based Graph Neural Networks for Semi-Supervised Learning	[paper]	[code]

---

graph pretrained model

title	paper link	code link
Graph-Bert: Only Attention is Needed for Learning Graph Representations	[paper]	[code(pytorch)]
Universal Graph Transformer Self-Attention Networks	[paper]	[code(pytorch)]
G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning	[paper]	[code]
A Generalization of Transformer Networks to Graphs	[paper]	[code(pytorch)]
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks	[paper]	[code(pytorch)]