Graph Models
Automated Graph Learning
Introduced by Li et al. in An adaptive graph learning method for automated molecular interactions and properties predictionsAutomated graph learning is a method that aims at discovering the best hyper-parameter and neural architecture configuration for different graph tasks/data without manual design.
Source: An adaptive graph learning method for automated molecular interactions and properties predictions
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Drug Discovery | 1 | 25.00% |
| Graph Learning | 1 | 25.00% |
| Graph Representation Learning | 1 | 25.00% |
| Molecular Property Prediction | 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 |
