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| 1.1 Why Graph Neural Network is important [ YOUTUBE ].html |
109б |
| 1. Graph Definition.mp4 |
23.89Мб |
| 1. Graph Definition.srt |
6.22Кб |
| 1. Graph Embedding Problem Statement.mp4 |
23.47Мб |
| 1. Graph Embedding Problem Statement.srt |
5.30Кб |
| 1. Review on Convolution Operation.mp4 |
43.28Мб |
| 1. Review on Convolution Operation.srt |
7.62Кб |
| 1. Review on Popular GNN Embedding Methods.mp4 |
39.86Мб |
| 1. Review on Popular GNN Embedding Methods.srt |
10.89Кб |
| 10.1 Workshop - SGC.py |
3.41Кб |
| 10. Workshop - SGC (Part A).mp4 |
150.85Мб |
| 10. Workshop - SGC (Part A).srt |
20.59Кб |
| 11. Workshop - SGC (Part B).mp4 |
181.03Мб |
| 11. Workshop - SGC (Part B).srt |
20.83Кб |
| 12.1 Detailed explanation of GCN paper [ YOUTUBE ].html |
104б |
| 12.2 SemiGCN.pdf |
853.42Кб |
| 12. Graph Convolution Network (GCN).mp4 |
109.91Мб |
| 12. Graph Convolution Network (GCN).srt |
23.91Кб |
| 13.1 Detailed explanation of GAT paper [ YOUTUBE ].html |
110б |
| 13.2 GAT.pdf |
1.56Мб |
| 13. Graph Attention Network.mp4 |
44.10Мб |
| 13. Graph Attention Network.srt |
9.45Кб |
| 2.1 DeppWalk.pdf |
801.74Кб |
| 2.1 ICASP 2020 Tutorial on Graph Convolution.html |
139б |
| 2. DeepWalk Algorithm.mp4 |
37.50Мб |
| 2. DeepWalk Algorithm.srt |
10.17Кб |
| 2. Graph Convolution (Signal Processing Point of View) Part A.mp4 |
90.74Мб |
| 2. Graph Convolution (Signal Processing Point of View) Part A.srt |
19.94Кб |
| 2. Storing Graph Information.mp4 |
29.19Мб |
| 2. Storing Graph Information.srt |
7.13Кб |
| 2. Transductive vs Inductive Embedding Methods.mp4 |
11.58Мб |
| 2. Transductive vs Inductive Embedding Methods.srt |
2.76Кб |
| 3.1 GraphSAGE.pdf |
964.84Кб |
| 3.1 ICASP 2020 Tutorial on Graph Convolution.html |
139б |
| 3.1 Workshop - DeepWalk_Karateclub.py |
1.66Кб |
| 3. Graph Convolution (Signal Processing Point of View) Part B.mp4 |
46.86Мб |
| 3. Graph Convolution (Signal Processing Point of View) Part B.srt |
10.99Кб |
| 3. Graph Degree and Laplacian of Graph.mp4 |
42.77Мб |
| 3. Graph Degree and Laplacian of Graph.srt |
7.78Кб |
| 3. GraphSAGE.mp4 |
45.75Мб |
| 3. GraphSAGE.srt |
10.97Кб |
| 3. Workshop - RandomWalk using karateclub library.mp4 |
243.78Мб |
| 3. Workshop - RandomWalk using karateclub library.srt |
29.34Кб |
| 4.1 A Literature Review on Graph Neural Networks [ YOUTUBE ].html |
110б |
| 4.1 n2vec.pdf |
781.44Кб |
| 4. Definition of Learning in Graph Representation Learning.mp4 |
30.91Мб |
| 4. Definition of Learning in Graph Representation Learning.srt |
7.41Кб |
| 4. Message Passing Framework.mp4 |
28.86Мб |
| 4. Message Passing Framework.srt |
6.21Кб |
| 4. Node2Vec Algorithm.mp4 |
16.94Мб |
| 4. Node2Vec Algorithm.srt |
4.13Кб |
| 5.1 Workshop - Node2Vec Using Karateclub.py |
2.55Кб |
| 5. Drawback in existing graph learning models.mp4 |
10.86Мб |
| 5. Drawback in existing graph learning models.srt |
1.94Кб |
| 5. Workshop - Node2Vec Using Karateclub.mp4 |
136.07Мб |
| 5. Workshop - Node2Vec Using Karateclub.srt |
12.62Кб |
| 6.1 Workshop - Node2Vec_TorchGeo.py |
2.94Кб |
| 6.1 Workshop - Using Torch and Torch Geometric for defining a graph.py |
1.88Кб |
| 6. Workshop - Node2Vec Using Pytorch Geometric (Part A).mp4 |
142.60Мб |
| 6. Workshop - Node2Vec Using Pytorch Geometric (Part A).srt |
19.84Кб |
| 6. Workshop - Using Torch and Torch Geometric for defining a graph.mp4 |
218.74Мб |
| 6. Workshop - Using Torch and Torch Geometric for defining a graph.srt |
26.28Кб |
| 7. Workshop - Node2Vec Using Pytorch Geometric (Part B).mp4 |
167.61Мб |
| 7. Workshop - Node2Vec Using Pytorch Geometric (Part B).srt |
18.42Кб |
| 8. GNN Motivation.mp4 |
25.70Мб |
| 8. GNN Motivation.srt |
5.22Кб |
| 9.1 SGC.pdf |
1.40Мб |
| 9. Simplifying Graph Convolution Network.mp4 |
41.22Мб |
| 9. Simplifying Graph Convolution Network.srt |
11.33Кб |
| Bonus Resources.txt |
357б |
| Get Bonus Downloads Here.url |
183б |