力荐一本最新的GNN书籍, 领域大牛云集~(附下载方式)

力荐一本最新的GNN书籍, 基本做GNN比较厉害的大佬全都参与了. 

从基础, 前沿到应用, 各种围绕GNN展开的研究全都有, 如节点/边/图级别任务, 同质/异质/动态图神经网络, 表示能力, 可解释性, AutoML, CV/NLP/推荐/药物等应用. 目前为止在图神经网络方面最为全面的一本书，希望能帮助大家更快更好的进入图神经网络这个领域。

  小编看了其中部分章节,感觉对GNN的理解更上一层~

开源网站：https://graph-neural-networks.github.io/index.html

懒人可去下面的QQ群文件下载。

内容介绍

本书主要分为3部分: Introduction, Foundations of Graph Neural Networks, 和 Frontiers of Graph Neural Networks.

Part I Introduction

本书将GNN归类到一种学习图表示的方法. 传统的矩阵分解, node2vec是浅层的图表示学习方法.

• 1 Representation Learning

• 2 Graph Representation Learning

• 3 Graph Neural Networks

Part II Foundations of Graph Neural Networks

本部分涵盖了GNN的基本任务, 表示能力(这部分力荐是Pan Li 和 Jure合著的), 大规模问题, 可解释性, 和鲁棒性.

• 4 Graph Neural Networks for Node Classification

• 5 The Expressive Power of Graph Neural Networks

• 6 Graph Neural Networks: Scalability

• 7 Interpretability in Graph Neural Networks

• 8 Graph Neural Networks: Adversarial Robustness

Part III Frontiers of Graph Neural Networks

这部分介绍了GNN在多种类型图(同质/异质/动态)上的多种任务(图分类/边预测/图生成/图结构学习等).

• 9 Graph Neural Networks: Graph Classification

• 10 Graph Neural Networks: Link Prediction

• 11 Graph Neural Networks: Graph Generation

• 12 Graph Neural Networks: Graph Transformation

• 13 Graph Neural Networks: Graph Matching

• 14 Graph Neural Networks: Graph Structure Learning

• 15 Dynamic Graph Neural Networks

• 16 Heterogeneous Graph Neural Networks

• 17 Graph Neural Networks: AutoML

• 18 Graph Neural Networks: Self-supervised Learning

Part IV Broad and Emerging Applications with Graph Neural Networks

这部分就是GNN的应用了.

• 19 Graph Neural Networks in Modern Recommender Systems .

• 20 Graph Neural Networks in Computer Vision

• 21 Graph Neural Networks in Natural Language Processing

• 22 Graph Neural Networks in Program Analysis

• 23 Graph Neural Networks in Software Mining

• 24 GNN-based Biomedical Knowledge Graph Mining in Drug Development

• 25 Graph Neural Networks in Predicting Protein Function and Interactions

• 26 Graph Neural Networks in Anomaly Detection 

• 27 Graph Neural Networks in Urban Intelligence

部分作者介绍

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