AAAI 2021 - Graph Neural Networks - Models and Applications 레퍼런스

Table of contents

1. Introduction
   1. Graphs and Graph Structured Data
   2. Tasks on Graph Structured Data
   3. Graph neural networks
2. Foundations
   1. Basic Graph Theory
   2. Graph Fourier Transform
3. Models
   1. Spectral-based GNN layers
   2. Spatial-based GNN layers
   3. Pooling Schemes for Graph-level Representation Learning
   4. Attacks and Robustness of Graph Neural Networks
   5. Deeper Graph Neural Networks
   6. Scalable Learning For Graph Neural Networks
   7. Self-supervised Learing for Graph Neural Networks
4. Applications
   1. Recommendation

링크

https://web.njit.edu/~ym329/tutorials/aaai2021/