Graph Models
Principal Neighbourhood Aggregation
Introduced by Corso et al. in Principal Neighbourhood Aggregation for Graph NetsPrincipal Neighbourhood Aggregation (PNA) is a general and flexible architecture for graphs combining multiple aggregators with degree-scalers (which generalize the sum aggregator).
Source: Principal Neighbourhood Aggregation for Graph Nets
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Computational Efficiency | 1 | 25.00% |
| Graph Classification | 1 | 25.00% |
| Graph Regression | 1 | 25.00% |
| Node Classification | 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 |
