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Related Questions
- Can you explain the concept of over-smoothing in the context of Graph Convolutional Networks (GCNs)?
- How does the spectral normalization affect the behavior of GCNs and contribute to over-smoothing?
- What are some common architectural modifications that can help mitigate over-smoothing in GCNs?
- In what scenarios is over-smoothing more likely to occur in GCNs, and how can it be detected?
- What are some alternative graph convolutional layers that can alleviate over-smoothing issues?
- Can you discuss the relationship between the number of layers and over-smoothing in GCNs?
- What are some strategies for adapting GCNs to handle nodes with varying degrees of significance or importance?
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