/GNN_paper_list

paper, code with respect to graph neural networks

Papers

Technical papers

2020

Title Conference/Journal Code
Measuring and Improving the Use of Graph Information in Graph Neural Networks ICLR Code
PairNorm: Tackling Oversmoothing in GNNs ICLR Code
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification ICLR Code
Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View ICLR
When Do GNNs Work: Understanding and Improving Neighborhood Aggregation
Graph Structure Learning for Robust Graph Neural Networks KDD Code

2019

Title Conference/Journal Code
How Powerful are Graph Neural Networks? ICLR Code
GNNExplainer: Generating Explanations for Graph Neural Networks NIPS Code
Understanding the Power of Graph Neural Networks in Learning Graph Topology NIPS Code
GeniePath: Graph Neural Networks with Adaptive Receptive Paths AAAI Code
Sparse Graph Attention Networks

2018

Title Conference/Journal Code
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling ICLR Code
Graph Attention Networks ICLR Code

2017

Title Conference/Journal Code
Semi-Supervised Classification with Graph Convolutional Networks ICLR Code
Inductive Representation Learning on Large Graphs NIPS http://snap.stanford.edu/graphsage/

Surveys

Title
Deep Learning on Graphs-A Survey
A Comprehensive Survey on Graph Neural Networks
Graph Neural Networks-A Review of Methods and Applications

Other resources

https://github.com/DeepGraphLearning/LiteratureDL4Graph
https://github.com/safe-graph/DGFraud
https://www.stellargraph.io/
https://awesomeopensource.com/projects/gcn?categoryPage=6
https://awesomeopensource.com/project/Jiakui/awesome-gcn