【斯坦福CS224W 2018秋&2019秋】图神经网络、图挖掘、网络分析[Jurij Leskovec] 英字
Jurij Leskovec亲自教授、GraphSage作者
视频选集
（11/22）
Lecture 01 - 09/25 Course Introduction and Structure of Graphs
01:16:43
Lecture 02 - 09/27 Measuring Networks, and Random Graph Model
01:18:52
Recitation 01 - 09/28 Introduction to SNAP.py
36:06
Lecture 03 - 10/02 Link Analysis: PageRank
01:22:54
Lecture 04 - 10/04 Network Construction, Inference, and Deconvolution
01:19:57
Recitation 02 - 10/05 Review of Linear Algebra, Probability, and Proof Technique
57:28
Lecture 05 - 10/09 Motifs and Graphlets
01:15:10
Lecture 06 - 10/11 Community Structure in Networks
01:12:54
Lecture 07 - 10/16 Community Detection: Spectral Clustering
01:21:45
Lecture 08 - 10/18 Link Prediction
01:14:25
Lecture 09 - 10/23 Graph Representation Learning
01:16:53
Lecture 10 - 10/25 Network Effects and Cascading Behavior (1)
01:16:48
Lecture 11 - 10/30 Network Effects and Cascading Behavior (2)
01:20:55
Lecture 12 - 11/01 Influence Maximization in Networks
01:18:29
Lecture 13 - 11/06 Outbreak Detection in Networks
01:15:12
Lecture 14 - 11/08 Network Robustness and Preferential Attachment
01:19:30
Lecture 15 - 11/13 Network Centrality
01:20:23
Lecture 16 - 11/15 Message Passing and Node Classification
01:19:10
Lecture 17 - 11/27 Network Evolution
01:23:43
Lecture 18 - 12/04 Knowledge Graphs and Metapaths
01:20:50
Lecture 19 - 12/06 Graph Convolutional Networks
01:28:05
Graph Node Embedding Algorithms (Stanford - Fall 2019)
01:25:51
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