Subgraph-Based Networks for Expressive, Efficient, and Domain-Independent Graph Learning

Subgraph-Based Networks for Expressive, Efficient, and Domain-Independent Graph Learning

IEEE Signal Processing Society via YouTube Direct link

Nodebased policies

20 of 29

20 of 29

Nodebased policies

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Classroom Contents

Subgraph-Based Networks for Expressive, Efficient, and Domain-Independent Graph Learning

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  1. 1 Introduction
  2. 2 Learning on graphs
  3. 3 Explicit power
  4. 4 Color refinement
  5. 5 Limitless exclusivity
  6. 6 Why exclusivity matters
  7. 7 Goal
  8. 8 Recipe
  9. 9 What is a suitable neural network
  10. 10 Equivariance
  11. 11 Equivariant
  12. 12 Benefits
  13. 13 Two kinds of symmetry
  14. 14 DSS
  15. 15 Architecture
  16. 16 Large graphs
  17. 17 Theoretical analysis
  18. 18 Experimental analysis
  19. 19 Evaliant graph networks
  20. 20 Nodebased policies
  21. 21 Tensors
  22. 22 Intuition
  23. 23 Other approaches
  24. 24 Sun architecture
  25. 25 Brain
  26. 26 Experiment
  27. 27 Summary
  28. 28 Conclusion
  29. 29 Questions

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