Image Classification on CIFAR-10 (test) (Baseline vs Pruned Performance)
94.48Baseline AccuracyPCC
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| PCCModel=ResNet-562026.01 | 94.48 | 93.13 | 1.35 | 61.64 | 65.06 | |
| CCMModel=ResNet-562026.01 | 93.75 | 92.74 | 1.01 | 69.9 | 70.3 | |
| FTWT_JModel=ResNet-562026.01 | 93.66 | 92.28 | 1.38 | 54 | — | |
| SCAPModel=ResNet-56, tau=0.52026.01 | 93.66 | 91.58 | 2.08 | 72.41 | 71.36 | |
| SCAPModel=ResNet-56, tau=0.62026.01 | 93.66 | 89.9 | 3.76 | 83.8 | 84.66 | |
| FPGMModel=ResNet-562026.01 | 93.59 | 93.49 | 0.1 | 52.6 | 50.6 | |
| DepGraphModel=ResNet-562026.01 | 93.53 | 93.77 | -0.24 | 52.4 | — | |
| FPRGModel=ResNet-562026.01 | 93.45 | 92.61 | 0.84 | 57.1 | 33.6 | |
| DTPModel=ResNet-562026.01 | 93.36 | 92.46 | 0.9 | 72.1 | — | |
| GAL-0.6Model=ResNet-562026.01 | 93.26 | 93.38 | -0.12 | 37.6 | 11.8 | |
| HRankModel=ResNet-562026.01 | 93.26 | 93.52 | -0.26 | 29.3 | 16.8 | |
| CHIPModel=ResNet-562026.01 | 93.26 | 94.16 | -0.9 | 47.4 | 42.8 | |
| CPModel=ResNet-562026.01 | 93.26 | 90.8 | 2.46 | 50.6 | — | |
| ℓ1-normModel=ResNet-562026.01 | 93.04 | 93.06 | -0.02 | 27.6 | 13.7 | |
| NISPModel=ResNet-562026.01 | 93.04 | 93.01 | 0.03 | 43.61 | 42.6 | |
| Li et al.Model=ResNet-562026.01 | 92.6 | 92.42 | 0.18 | 49.9 | 44 |