Graph Models
MinCut Pooling
Introduced by Bianchi et al. in Spectral Clustering with Graph Neural Networks for Graph PoolingMinCutPool is a trainable pooling operator for graphs that learns to map nodes into clusters. The method is trained to approximate the minimum K-cut of the graph to ensure that the clusters are balanced, while also jointly optimizing the objective of the task at hand.
Source: Spectral Clustering with Graph Neural Networks for Graph Pooling
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Clustering | 1 | 25.00% |
| Graph Classification | 1 | 25.00% |
| Graph Clustering | 1 | 25.00% |
| Semantic Segmentation | 1 | 25.00% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
