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Graph Neural Networks
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Classroom Contents
Bastian Rieck - Topological Graph Neural Networks
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- 1 Introduction
- 2 Representation of graphs
- 3 Graph similarity analysis
- 4 Modern graph neural networks
- 5 Status quo
- 6 Topological features
- 7 Persistent homology
- 8 The choice of filtration
- 9 Graph Neural Networks
- 10 Multifiltration Learning
- 11 Theoretical Nuggets
- 12 Nonisomorphic Graphs
- 13 Experiments
- 14 Synthetic Data Sets
- 15 WL Test
- 16 Results
- 17 Removing node attributes
- 18 Comparing results
