Model Compression
Pruning
Introduced by Li et al. in Pruning Filters for Efficient ConvNetsPapers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Network Pruning | 44 | 7.91% |
| Quantization | 38 | 6.83% |
| Model Compression | 33 | 5.94% |
| Language Modelling | 31 | 5.58% |
| Image Classification | 25 | 4.50% |
| Federated Learning | 22 | 3.96% |
| Computational Efficiency | 17 | 3.06% |
| Large Language Model | 10 | 1.80% |
| Question Answering | 10 | 1.80% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
