Graph Models
ARMA GNN
Introduced by Bianchi et al. in Graph Neural Networks with convolutional ARMA filtersThe ARMA GNN layer implements a rational graph filter with a recursive approximation.
Source: Graph Neural Networks with convolutional ARMA filters
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Time Series Analysis | 8 | 24.24% |
| Management | 3 | 9.09% |
| Time Series Forecasting | 2 | 6.06% |
| Future prediction | 1 | 3.03% |
| Bayesian Optimization | 1 | 3.03% |
| BIG-bench Machine Learning | 1 | 3.03% |
| Feature Engineering | 1 | 3.03% |
| energy management | 1 | 3.03% |
| Model Predictive Control | 1 | 3.03% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
