Stochastic Optimization
Gravity
Introduced by Bahrami et al. in Gravity Optimizer: a Kinematic Approach on Optimization in Deep LearningGravity is a kinematic approach to optimization based on gradients.
Source: Gravity Optimizer: a Kinematic Approach on Optimization in Deep Learning
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Deep Learning | 7 | 4.79% |
| Reinforcement Learning (RL) | 5 | 3.42% |
| Translation | 5 | 3.42% |
| Prediction | 4 | 2.74% |
| Uncertainty Quantification | 4 | 2.74% |
| Object | 4 | 2.74% |
| Pose Estimation | 4 | 2.74% |
| regression | 3 | 2.05% |
| Operator learning | 3 | 2.05% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
