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  1. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 10.1-Heterogeneous & Knowledge Graph Embedding [Rfkntma6ZUI].mp4 +2 -2
  2. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 10.3 - Knowledge Graph Completion Algorithms [Xm5VrxZYhu4].mp4 +1 -1
  3. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 12.1-Fast Neural Subgraph Matching & Counting [lRCDpfJoMiE].mp4 +2 -2
  4. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 13.1 - Community Detection in Networks [KXi4ha79o3s].mp4 +2 -2
  5. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 13.4 - Detecting Overlapping Communities [SHcVHrsgj8w].mp4 +2 -2
  6. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.1 - Deep Generative Models for Graphs [IMpkHvQ0LA4].mp4 +2 -2
  7. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.2 - Graph RNN： Generating Realistic Graphs [xGDUYQGvRac].mp4 +2 -2
  8. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.3 - Scaling Up & Evaluating Graph Gen [kDu5YY9d1TM].mp4 +2 -2
  9. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 15.4 - Applications of Deep Graph Generation [SdBk8fMmwUU].mp4 +2 -2
  10. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 17.1 - Scaling up Graph Neural Networks [2nPCw3yHlnI].mp4 +2 -2
  11. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 2.2 - Traditional Feature-based Methods： Link [4dVwlE9jYxY].mp4 +2 -2
  12. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 6.1 - Introduction to Graph Neural Networks [F3PgltDzllc].mp4 +1 -1
  13. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 9.1 - How Expressive are Graph Neural Networks [5vMEgYbka0A].mp4 +2 -2
  14. MLwG/Stanford CS224W： ML with Graphs ｜ 2021 ｜ Lecture 9.2 - Designing the Most Powerful GNNs [B5y47gWt3co].mp4 +2 -2
  15. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.2 - Applications of Graph ML [aBHC6xzx9YI].mp4 +1 -1
  16. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 1.3 - Choice of Graph Representation​ [P-m1Qv6-8cI].mp4 +1 -1
  17. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 11.1 - Reasoning in Knowledge Graphs [X9yl0pTP9fY].mp4 +2 -2
  18. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 11.2 - Answering Predictive Queries [qaRIBNE-4Ho].mp4 +2 -2
  19. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 11.3 - Query2box： Reasoning over KGs [Nt66M2OsbCw].mp4 +2 -2
  20. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 12.2 - Neural Subgraph Matching [4Ia5QzQ_QNI].mp4 +2 -2
  21. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 12.3 - Finding Frequent Subgraphs [kUv4gY5e0hg].mp4 +2 -2
  22. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 13.2 - Network Communities [mJQrtXZT5pw].mp4 +2 -2
  23. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 13.3 - Louvain Algorithm [0zuiLBOIcsw].mp4 +2 -2
  24. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 14.4 - Kronecker Graph Model [Xnpt8US31cQ].mp4 +2 -2
  25. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 17.2 - GraphSAGE Neighbor Sampling [LLUxwHc7O4A].mp4 +2 -2
  26. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 17.3 - Cluster GCN： Scaling up GNNs [RJkR8Ig6dXI].mp4 +2 -2
  27. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 17.4 - Scaling up by Simplifying GNNs [iTRW9Gh7yKI].mp4 +2 -2
  28. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 4.3 - Random Walk with Restarts [HbzQzUaJ_9I].mp4 +2 -2
  29. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 6.2 - Basics of Deep Learning [tutlI9YzJ2g].mp4 +1 -1
  30. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 6.3 - Deep Learning for Graphs [MH4yvtgAR-4].mp4 +2 -2
  31. MLwG/Stanford CS224W： Machine Learning with Graphs ｜ 2021 ｜ Lecture 8.3 - Setting up GNN Prediction Tasks [ewEW_EMzRuo].mp4 +2 -2
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