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Stanford CS224W: Machine Learning with Graphs

by Stanford Online · 60 videos

Total watch time

22h 23m

at 1× speed · exactly 22 hours, 23 minutes, 15 seconds at 1×

1×22h 23m 15s
1.25×17h 54m 36s
1.5×14h 55m 30s
1.75×12h 47m 34s
2×11h 11m 38s
Average video22m 23s
Longest1h 21m 19s
Shortest5m 51s
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Videos (60)

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1 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.1 - Why Graphs 11:55 2021-04-13
2 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.2 - Applications of Graph ML 20:27 2021-04-13
3 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.3 - Choice of Graph Representation​ 20:27 2021-04-13
4 Stanford CS224W: ML with Graphs | 2021 | Lecture 2.1 - Traditional Feature-based Methods: Node 27:30 2021-04-15
5 Stanford CS224W: ML with Graphs | 2021 | Lecture 2.2 - Traditional Feature-based Methods: Link 16:47 2021-04-15
6 Stanford CS224W: ML with Graphs | 2021 | Lecture 2.3 - Traditional Feature-based Methods: Graph 20:10 2021-04-15
7 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 3.1 - Node Embeddings 14:44 2021-04-20
8 Stanford CS224W: ML with Graphs | 2021 | Lecture 3.2-Random Walk Approaches for Node Embeddings 27:07 2021-04-20
9 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 3.3 - Embedding Entire Graphs 18:04 2021-04-20
10 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.1 - PageRank 27:10 2021-04-22
11 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.2 - PageRank: How to Solve? 20:41 2021-04-22
12 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.3 - Random Walk with Restarts 13:31 2021-04-22
13 Stanford CS224W: ML with Graphs | 2021 | Lecture 4.4 - Matrix Factorization and Node Embeddings 12:48 2021-04-22
14 Stanford CS224W: ML with Graphs | 2021 | Lecture 5.1 - Message passing and Node Classification 18:34 2021-04-27
15 Stanford CS224W: ML with Graphs | 2021 | Lecture 5.2 - Relational and Iterative Classification 29:20 2021-04-27
16 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 5.3 - Collective Classification 24:26 2021-04-27
17 Stanford CS224W: ML with Graphs | 2021 | Lecture 6.1 - Introduction to Graph Neural Networks 10:31 2021-04-29
18 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.2 - Basics of Deep Learning 29:31 2021-04-29
19 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.3 - Deep Learning for Graphs 35:41 2021-04-29
20 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.1 - A general Perspective on GNNs 5:51 2021-05-04
21 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.2 - A Single Layer of a GNN 40:09 2021-05-04
22 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.3 - Stacking layers of a GNN 18:11 2021-05-04
23 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.1 - Graph Augmentation for GNNs 27:50 2021-05-06
24 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.2 - Training Graph Neural Networks 40:19 2021-05-06
25 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.3 - Setting up GNN Prediction Tasks 17:49 2021-05-06
26 Stanford CS224W: ML with Graphs | 2021 | Lecture 9.1 - How Expressive are Graph Neural Networks 25:21 2021-05-11
27 Stanford CS224W: ML with Graphs | 2021 | Lecture 9.2 - Designing the Most Powerful GNNs 31:52 2021-05-11
28 Stanford CS224W: ML with Graphs | 2021 | Lecture 10.1-Heterogeneous & Knowledge Graph Embedding 34:57 2021-05-13
29 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 10.2 - Knowledge Graph Completion 7:16 2021-05-13
30 Stanford CS224W: ML with Graphs | 2021 | Lecture 10.3 - Knowledge Graph Completion Algorithms 34:31 2021-05-13
31 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 11.1 - Reasoning in Knowledge Graphs 16:53 2021-05-18
32 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 11.2 - Answering Predictive Queries 12:39 2021-05-18
33 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 11.3 - Query2box: Reasoning over KGs 38:20 2021-05-18
34 Stanford CS224W: ML with Graphs | 2021 | Lecture 12.1-Fast Neural Subgraph Matching & Counting 35:40 2021-05-20
35 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 12.2 - Neural Subgraph Matching 24:54 2021-05-17
36 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 12.3 - Finding Frequent Subgraphs 25:54 2021-05-20
37 Stanford CS224W: ML with Graphs | 2021 | Lecture 13.1 - Community Detection in Networks 22:14 2021-05-25
38 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 13.2 - Network Communities 17:41 2021-05-25
39 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 13.3 - Louvain Algorithm 15:20 2021-05-25
40 Stanford CS224W: ML with Graphs | 2021 | Lecture 13.4 - Detecting Overlapping Communities 23:57 2021-05-25
41 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.1 - Generative Models for Graphs 20:28 2021-05-27
42 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.2 - Erdos Renyi Random Graphs 20:00 2021-05-27
43 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.3 - The Small World Model 10:29 2021-05-27
44 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.4 - Kronecker Graph Model 18:03 2021-05-27
45 Stanford CS224W: ML with Graphs | 2021 | Lecture 15.1 - Deep Generative Models for Graphs 15:44 2021-06-01
46 Stanford CS224W: ML with Graphs | 2021 | Lecture 15.2 - Graph RNN: Generating Realistic Graphs 24:52 2021-06-01
47 Stanford CS224W: ML with Graphs | 2021 | Lecture 15.3 - Scaling Up & Evaluating Graph Gen 15:29 2021-06-01
48 Stanford CS224W: ML with Graphs | 2021 | Lecture 15.4 - Applications of Deep Graph Generation 13:35 2021-06-01
49 Stanford CS224W: ML with Graphs | 2021 | Lecture 16.1 - Limitations of Graph Neural Networks 11:10 2021-06-03
50 Stanford CS224W: ML with Graphs | 2021 | Lecture 16.2 - Position-Aware Graph Neural Networks 12:41 2021-06-03
51 Stanford CS224W: ML with Graphs | 2021 | Lecture 16.3 - Identity-Aware Graph Neural Networks 20:01 2021-06-03
52 Stanford CS224W: ML with Graphs | 2021 | Lecture 16.4 - Robustness of Graph Neural Networks 22:39 2021-06-03
53 Stanford CS224W: ML with Graphs | 2021 | Lecture 17.1 - Scaling up Graph Neural Networks 14:51 2021-06-08
54 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.2 - GraphSAGE Neighbor Sampling 16:50 2021-06-08
55 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.3 - Cluster GCN: Scaling up GNNs 19:18 2021-06-08
56 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.4 - Scaling up by Simplifying GNNs 18:40 2021-06-08
57 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 18 - GNNs in Computational Biology 1:21:19 2021-06-10
58 Stanford CS224W: ML with Graphs | 2021 | Lecture 19.1 - Pre-Training Graph Neural Networks 20:07 2021-06-15
59 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 19.2 - Hyperbolic Graph Embeddings 31:47 2021-06-15
60 Stanford CS224W: ML with Graphs | 2021 | Lecture 19.3 - Design Space of Graph Neural Networks 18:10 2021-06-15

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