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  1. MLwG/Lecture 1 - Deep Learning Foundations： review of basic DL models and optimization solvers [6Nctj1GCFVo].en.vtt +0 -0
  2. MLwG/Lecture 1 - Deep Learning Foundations： review of basic DL models and optimization solvers [6Nctj1GCFVo].webp +3 -0
  3. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 10.1-Heterogeneous & Knowledge Graph Embedding [Rfkntma6ZUI].mp4 +3 -0
  4. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 10.3 - Knowledge Graph Completion Algorithms [Xm5VrxZYhu4].mp4 +3 -0
  5. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 12.1-Fast Neural Subgraph Matching & Counting [lRCDpfJoMiE].mp4 +3 -0
  6. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 13.1 - Community Detection in Networks [KXi4ha79o3s].mp4 +3 -0
  7. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 13.4 - Detecting Overlapping Communities [SHcVHrsgj8w].mp4 +3 -0
  8. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.1 - Deep Generative Models for Graphs [IMpkHvQ0LA4].mp4 +3 -0
  9. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.2 - Graph RNN： Generating Realistic Graphs [xGDUYQGvRac].mp4 +3 -0
  10. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.3 - Scaling Up & Evaluating Graph Gen [kDu5YY9d1TM].mp4 +3 -0
  11. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.4 - Applications of Deep Graph Generation [SdBk8fMmwUU].mp4 +3 -0
  12. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 16.1 - Limitations of Graph Neural Networks [yT5PziOXxQg].mp4 +3 -0
  13. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 16.2 - Position-Aware Graph Neural Networks [6ZFvToZUjGA].mp4 +3 -0
  14. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 16.3 - Identity-Aware Graph Neural Networks [SJqWQGh__N8].mp4 +3 -0
  15. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 16.4 - Robustness of Graph Neural Networks [uBmtTL3EitI].mp4 +3 -0
  16. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 17.1 - Scaling up Graph Neural Networks [2nPCw3yHlnI].mp4 +3 -0
  17. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 19.1 - Pre-Training Graph Neural Networks [JDW82csukhE].mp4 +3 -0
  18. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 19.3 - Design Space of Graph Neural Networks [8OhnwzT9ypg].mp4 +3 -0
  19. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 2.1 - Traditional Feature-based Methods： Node [3IS7UhNMQ3U].mp4 +3 -0
  20. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 2.2 - Traditional Feature-based Methods： Link [4dVwlE9jYxY].mp4 +3 -0
  21. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 2.3 - Traditional Feature-based Methods： Graph [buzsHTa4Hgs].mp4 +3 -0
  22. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 3.2-Random Walk Approaches for Node Embeddings [Xv0wRy66Big].mp4 +3 -0
  23. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 4.4 - Matrix Factorization and Node Embeddings [r12qJZZVtqc].mp4 +3 -0
  24. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 5.1 - Message passing and Node Classification [6g9vtxUmfwM].mp4 +3 -0
  25. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 5.2 - Relational and Iterative Classification [QUO-HQ44EDc].mp4 +3 -0
  26. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 6.1 - Introduction to Graph Neural Networks [F3PgltDzllc].mp4 +3 -0
  27. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 9.1 - How Expressive are Graph Neural Networks [5vMEgYbka0A].mp4 +3 -0
  28. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 9.2 - Designing the Most Powerful GNNs [B5y47gWt3co].mp4 +3 -0
  29. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.1 - Why Graphs [JAB_plj2rbA].mp4 +3 -0
  30. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.2 - Applications of Graph ML [aBHC6xzx9YI].mp4 +3 -0
  31. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.3 - Choice of Graph Representation​ [P-m1Qv6-8cI].mp4 +3 -0
  32. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 10.2 - Knowledge Graph Completion [xop5tC9T5xM].mp4 +3 -0
  33. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 11.1 - Reasoning in Knowledge Graphs [X9yl0pTP9fY].mp4 +3 -0
  34. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 11.2 - Answering Predictive Queries [qaRIBNE-4Ho].mp4 +3 -0
  35. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 11.3 - Query2box： Reasoning over KGs [Nt66M2OsbCw].mp4 +3 -0
  36. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 12.2 - Neural Subgraph Matching [4Ia5QzQ_QNI].mp4 +3 -0
  37. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 12.3 - Finding Frequent Subgraphs [kUv4gY5e0hg].mp4 +3 -0
  38. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 13.2 - Network Communities [mJQrtXZT5pw].mp4 +3 -0
  39. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 13.3 - Louvain Algorithm [0zuiLBOIcsw].mp4 +3 -0
  40. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 14.1 - Generative Models for Graphs [OhjXpYIo9h4].mp4 +3 -0
  41. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 14.2 - Erdos Renyi Random Graphs [VC43S6Thwg0].mp4 +3 -0
  42. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 14.4 - Kronecker Graph Model [Xnpt8US31cQ].mp4 +3 -0
  43. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 17.2 - GraphSAGE Neighbor Sampling [LLUxwHc7O4A].mp4 +3 -0
  44. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 17.3 - Cluster GCN： Scaling up GNNs [RJkR8Ig6dXI].mp4 +3 -0
  45. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 17.4 - Scaling up by Simplifying GNNs [iTRW9Gh7yKI].mp4 +3 -0
  46. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 18 - GNNs in Computational Biology [_hy9AgZXhbQ].mp4 +3 -0
  47. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 19.2 - Hyperbolic Graph Embeddings [m2zoddmgvd0].mp4 +3 -0
  48. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 3.1 - Node Embeddings [rMq21iY61SE].mp4 +3 -0
  49. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 3.3 - Embedding Entire Graphs [eliMLfJeu7A].mp4 +3 -0
  50. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 4.1 - PageRank [TU0ankRcHmo].mp4 +3 -0
MLwG/Lecture 1 - Deep Learning Foundations： review of basic DL models and optimization solvers [6Nctj1GCFVo].en.vtt ADDED
The diff for this file is too large to render. See raw diff
 
MLwG/Lecture 1 - Deep Learning Foundations： review of basic DL models and optimization solvers [6Nctj1GCFVo].webp ADDED

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