Graph Models
Adaptive Graph Convolutional Neural Networks
Introduced by Li et al. in Adaptive Graph Convolutional Neural NetworksAGCN is a novel spectral graph convolution network that feed on original data of diverse graph structures.
Image credit: Adaptive Graph Convolutional Neural Networks
Source: Adaptive Graph Convolutional Neural Networks
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Event data classification | 1 | 8.33% |
| Graph Representation Learning | 1 | 8.33% |
| Scene Classification | 1 | 8.33% |
| Scene Recognition | 1 | 8.33% |
| Scene Understanding | 1 | 8.33% |
| Clustering | 1 | 8.33% |
| Deep Clustering | 1 | 8.33% |
| Graph Clustering | 1 | 8.33% |
| Graph Embedding | 1 | 8.33% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
