Literature Survey in Pooling

[AnimeshSinha1309]

• [ ] 1. Hierarchical Pooling in Graph Neural Networks to Enhance Classification Performance in Large Datasets
• [ ] 2. Hierarchical Graph Pooling with Structure Learning (Code)
• [ ] 3. SimPool: Towards Topology Based Graph Pooling with Structural Similarity Features
• [x] 4. Hierarchical Graph Representation Learning with Differentiable Pooling - Diff pool
• [x] 5. Spectral Clustering with Graph Neural Networks for Graph Pooling - MinCut pool
• [ ] 6. Self-Attention Graph Pooling
• [ ] 7. Path Integral Based Convolution and Pooling for Graph Neural Networks - PAN pool
• [ ] 8. Multi-Channel Pooling Graph Neural Networks - Much pool
• [ ] 9. Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling
• [ ] 10. Graph Pooling via Coarsened Graph Infomax
• [x] 11. ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
• [ ] 12. Graph Convolutional Networks with EigenPooling
• [ ] 13. Hierarchically Attentive Graph Pooling with Subgraph Attention
• [ ] 14. Rethinking pooling in graph neural networks

[AnimeshSinha1309]

SIGN: Scalable Inception Graph Neural Networks - paper on using convolutions of different sizes to sidestep sampling in huge graphs.

[AnimeshSinha1309]

Things to take special note of:

• Try to see what are the tasks and benchmarks that people are approaching
• Highlight the formulae and important theoretical ideas
• Make some flow of results and a comparative across the papers, and competitor papers on those results