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!