Machine Learning with Graphs

Machine Learning with Graphs

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Stanford CS224W: ML with Graphs | 2021 | Lecture 2.3 - Traditional Feature-based Methods: Graph

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Stanford CS224W: ML with Graphs | 2021 | Lecture 2.3 - Traditional Feature-based Methods: Graph

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Machine Learning with Graphs

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

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