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