Image Classification on CIFAR-100 (Adversarial Robustness Metrics)
19.99Acc (FGSM, 8/255)FxTS-Net
Evaluation results
| Method | Links | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FxTS-Net2025.09 | 19.99 | 18.63 | 20.69 | 20.25 | 48.9 | 35.94 | 18.66 | 18.26 | 12.53 | 9.67 | 22.35 | |
| Zubov-Net2025.09 | 19.53 | 17.29 | 22.33 | 22.14 | 44.47 | 31.83 | 20.52 | 20.22 | 16.44 | 13.02 | 22.78 | |
| Proj-NODE2025.09 | 18.86 | 17.51 | 20.76 | 20.46 | 41.71 | 29.95 | 18.92 | 18.71 | 8.82 | 4.51 | 20.02 | |
| LyaNet2025.09 | 18.3 | 16.32 | 21.27 | 21.03 | 46.09 | 33.18 | 19.26 | 18.94 | 12.85 | 9.52 | 21.68 | |
| SODEF2025.09 | 17.57 | 15.83 | 21.33 | 21.17 | 40.38 | 26.97 | 19.47 | 18.86 | 7.78 | 4.06 | 19.34 | |
| ResNet182025.09 | 16.97 | 13.93 | 21.47 | 21.4 | 37.15 | 22.78 | 19.52 | 19.27 | 7.36 | 3.89 | 18.37 | |
| Neural ODE2025.09 | 16.24 | 13.58 | 20.97 | 20.62 | 36.9 | 22.86 | 18.78 | 18.36 | 7.01 | 3.71 | 17.9 |