CS224W摘要总纲（已完结）

Posted 2022-12-12 oldmao_2000

文章目录

• [01.Introduction；Machine Learning for Graphs](https://blog.csdn.net/oldmao_2001/article/details/120067969)
• [02.Traditional Methods for Machine Learning in Graphs](https://blog.csdn.net/oldmao_2001/article/details/120119282)
• [03.Node Embedding](https://blog.csdn.net/oldmao_2001/article/details/120247466)
• [04.Link Analysis: PageRank](https://blog.csdn.net/oldmao_2001/article/details/120253335)
• [05.Label Propagation for Node Classification](https://blog.csdn.net/oldmao_2001/article/details/120310357)
• 06.07.GNN
• [08.Applications of Graph Neural Networks](https://blog.csdn.net/oldmao_2001/article/details/120403754)
• [09.Theory of Graph Neural Networks](https://blog.csdn.net/oldmao_2001/article/details/120468742)
• [10.Knowledge Graph Embeddings](https://blog.csdn.net/oldmao_2001/article/details/120475981)
• [11.Reasoning over Knowledge Graphs](https://blog.csdn.net/oldmao_2001/article/details/120509854)
• [12.Frequent Subgraph Mining with GNNs](https://blog.csdn.net/oldmao_2001/article/details/120567527)
• [13.Community Detection in Networks](https://blog.csdn.net/oldmao_2001/article/details/120607166)
• [14.Traditional Generative Models for Graphs](https://blog.csdn.net/oldmao_2001/article/details/120642481)
• [15.Deep Generative Models for Graphs](https://blog.csdn.net/oldmao_2001/article/details/120673776)
• [16.Advanced Topics on GNNs](https://blog.csdn.net/oldmao_2001/article/details/120700381)
• [17.Scaling Up GNNs](https://blog.csdn.net/oldmao_2001/article/details/120730080)
• [Graph Neural Networks in Computational Biology](https://blog.csdn.net/oldmao_2001/article/details/120810623)
• [19.GNNs for Science](https://blog.csdn.net/oldmao_2001/article/details/120905267)

CS224W: Machine Learning with Graphs
公式输入请参考： 在线Latex公式

01.Introduction；Machine Learning for Graphs

Why Graphs?
Applications of Graph ML
Choice of Graph Representation

02.Traditional Methods for Machine Learning in Graphs

Node-level Tasks and Features
Link Prediction Task and Feature
Graph-Level Features and Graph Kernels

03.Node Embedding

Encoder 和Decoder框架
随机游走
Node2Vec
Embedding entire graphs

04.Link Analysis: PageRank

PageRank介绍
How to solve PageRank?
Random Walk with restarts and Personalized PageRank
Matrix Factorization and Node Embeddings
Limitations of node embeddings via matrix factorization and random walks

05.Label Propagation for Node Classification

Homophily和Influence
Probabilistic Relational classifiers
Iterative classification
Belief Propagation

06.07.GNN

Basic of Deep Learning（略）
Deep Learning for Graphs

08.Applications of Graph Neural Networks

Graph Feature augmentation
Graph Structure augmentation
Prediction with GNNs
Training Graph Neural Networks
Setting-up GNN Prediction Tasks

09.Theory of Graph Neural Networks

How powerful are GNNs?
    local neighborhood structures
    lComputational graph
Injective Function
    lDesigning the Most Powerful Graph Neural Network
    linjective multiset function
    lGIN vs WL graph Kernel

10.Knowledge Graph Embeddings

Heterogeneous Graphs and Relational GCN (RGCN)
Knowledge Graphs: KG Completion with Embeddings
Knowledge Graph Completion: TransE, TransR, DistMult, ComplEx

11.Reasoning over Knowledge Graphs

Reasoning over Knowledge Graphs
Answering Predictive Queries on Knowledge Graphs
Query2box: Reasoning over KGs Using Box Embeddings
AND-OR queries

12.Frequent Subgraph Mining with GNNs

Subgraph and Motifs
Neural Subgraph Matching / Representations
Mining / Finding Frequent Motifs / Subgraphs

13.Community Detection in Networks

Community Detection in Networks
Network Communites
Louvain Algorithm
Detecting Overlapping Communities: BigCLAM

14.Traditional Generative Models for Graphs

Properties of Real-world Graphs
MSN Graph
Erdös-Renyi Random Graphs
The Small-World Model
Kronecker Graph Model

15.Deep Generative Models for Graphs

Graph Generative Models
GraphRNN
深度图生成模型的应用（药物）

16.Advanced Topics on GNNs

Limitations of GNN
Position-aware GNNs
Identity-aware GNNs
GNN的鲁棒性

17.Scaling Up GNNs

Scaling Up GNNs to Large Graphs
Neighbor Sampling: GraphSAGE
Cluster-GCN
Simplified GCN

Graph Neural Networks in Computational Biology

背景介绍
药物及药物组合的安全性
患者预后及疾病分类
新药研发

19.GNNs for Science

Pre-Training GNN
Hyperbolic Graph Embeddings
Design Space of GNN