On the Complexity of Optimal Graph Rewiring for Oversmoothing and Oversquashing in Graph Neural Networks

1. 1Identify the graph structure that leads to oversmoothing and oversquashing
2. 2Analyze the complexity of optimal graph rewiring to mitigate these issues
3. 3Develop algorithms to optimize the graph topology for better node representation and information propagation
4. 4Evaluate the performance of the optimized graph structure on various benchmarks

AI engineers and researchers working on Graph Neural Networks can benefit from this research to improve the performance of their models, and software engineers can apply these findings to develop more efficient graph-based algorithms

💡 Optimizing graph topology can help alleviate oversmoothing and oversquashing in Graph Neural Networks

🤖 Optimize graph topology to mitigate oversmoothing & oversquashing in GNNs!