# Reading list of Graph Representation Learning

A reading list of adversarial learning on graphs, it will keep updated on Github(awesome-graph-representation-learning). Welcome Pull requests and Stars!

## Papers

### Graph representation learning

- Deep Convolutional Networks on Graph-Structured Data, Mikael Henaff et al., arXiv 2015
- Representation Learning on Graphs: Methods and Applications, William L. Hamilton et al., arXiv 2018
- Deep Learning on Graphs: A Survey, Ziwei Zhang et al., arXiv 2018
- Graph Neural Networks: A Review of Methods and Applications, Jie Zhou et al., arXiv 2019
- A Comprehensive Survey on Graph Neural Networks, Zonghan Wu et al., arXiv 2019
- A Structural Graph Representation Learning Framework, Ryan A. Rossi et al., WSDM 2020
- Initialization for Network Embedding: A Graph Partition Approach, Wenqing Lin et al., WSDM 2020
- Dynamic graph representation learning via self-attention networks, Aravind Sankar et al., WSDM 2020
- Relation Learning on Social Networks with Multi-Modal Graph Edge Variational Autoencoders, Carl Yang et al., WSDM 2020
- Robust Graph Neural Network Against Poisoning Attacks via Transfer Learning, Xianfeng Tang et al., WSDM 2020

### Adversarial learning on graphs

- Intriguing properties of neural networks, Christian Szegedy et al., arXiv 2014
- Explaining and Harnessing Adversarial Examples, Ian J. Goodfellow et al., ICLR 2015
- Motivating the Rules of the Game for Adversarial Example Research, Justin Gilmer et al., arXiv 2018
- Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning, Battista Biggio et al., arXiv 2018
- Adversarial Attack on Graph Structured Data, Hanjun Dai et al., ICML 2018
- Adversarial Attacks on Neural Networks for Graph Data, Daniel Zügner et al., KDD 2018
- Adversarial Attacks on Node Embeddings, Aleksandar Bojchevski et al., arXiv 2018
- Data Poisoning Attack against Unsupervised Node Embedding Methods, Mingjie Sun et al., arXiv 2018
- Attack Graph Convolutional Networks by Adding Fake Nodes, Xiaoyun Wang et al., arXiv 2018
- Link prediction adversarial attack, Jinyin Chen et al., arXiv 2018
- Fast gradient attack on network embedding, Jinyin Chen et al., arXiv 2018
- Characterizing Malicious Edges targeting on Graph Neural Networks, Xiaojun Xu et al., openreview 2018
- Adversarial Attacks on Graph Neural Networks via Meta Learning, Daniel Zügner et al., ICLR 2019

## Tutorials and Workshops

### Graph representation learning

- KDD 2018 Graph Representation Tutorial
- WWW 2018 Representation Learning on Networks Tutorial
- AAAI 2019 Graph Representation Learning Tutorial

### Adversarial learing

- NeurIPS 2016 Workshop on Adversarial Training
- AAAI 2018 Adversarial machine learning tutorial
- AAAI 2019 Adversarial machine learning tutorial

Github on(awesome-graph-representation-learning). Welcome Pull requests and Stars!