Model Compression
Pruning
Introduced by Li et al. in Pruning Filters for Efficient ConvNetsPapers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Quantization | 47 | 7.51% |
| Language Modelling | 38 | 6.07% |
| Model Compression | 32 | 5.11% |
| Network Pruning | 28 | 4.47% |
| Large Language Model | 22 | 3.51% |
| Federated Learning | 22 | 3.51% |
| Image Classification | 17 | 2.72% |
| Computational Efficiency | 14 | 2.24% |
| Image Generation | 10 | 1.60% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
