Image Classification on CIFAR-10 (Noise Robustness)
91.45Accuracy (Original)Neural ODE
Evaluation results
| Method | Links | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Neural ODEActivation=Tanh2025.09 | 91.45 | 68.62 | 71.12 | 62.46 | 77.15 | 75.96 | 78.82 | 81.6 | 79.32 | 74.38 | |
| Zubov-NetActivation=Tanh2025.09 | 91.29 | 71.06 | 76.43 | 66.71 | 81.9 | 78.8 | 82.86 | 86 | 84.92 | 78.59 | |
| ResNet182025.09 | 91.11 | 68.28 | 68.36 | 62.84 | 76.77 | 75.41 | 77.63 | 82.08 | 78.01 | 73.67 | |
| SODEFActivation=sin2025.09 | 90.19 | 69.2 | 73.65 | 63.88 | 81.14 | 77.85 | 82.61 | 86.14 | 85.35 | 77.48 | |
| Proj-NODEActivation=Tanh2025.09 | 90.03 | 68.69 | 71.51 | 62.87 | 80.34 | 77.4 | 80.18 | 85.38 | 83.29 | 76.21 | |
| FxTS-Net2025.09 | 88.52 | 68.78 | 72.76 | 64.02 | 80.24 | 77.74 | 80.73 | 85.19 | 83.79 | 76.66 | |
| LyaNet2025.09 | 88.34 | 67.35 | 71.35 | 63.38 | 80.11 | 76.51 | 79.36 | 85.07 | 83.53 | 75.83 |