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 | 7.93% |
| Quantization | 39 | 7.03% |
| Model Compression | 33 | 5.95% |
| Language Modelling | 30 | 5.41% |
| Image Classification | 25 | 4.50% |
| Federated Learning | 21 | 3.78% |
| 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 |
