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 |
|---|---|---|
| Translation | 4 | 4.26% |
| Reinforcement Learning (RL) | 3 | 3.19% |
| Management | 3 | 3.19% |
| 3D Reconstruction | 3 | 3.19% |
| Pose Estimation | 3 | 3.19% |
| Point Cloud Registration | 2 | 2.13% |
| Decision Making | 2 | 2.13% |
| Optical Flow Estimation | 2 | 2.13% |
| Depth Estimation | 2 | 2.13% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
