| image-classification-on-clothing1m | DivideMix | #14 | Accuracy: 74.76% |
| image-classification-on-mini-webvision-1-0 | DivideMix (Inception-ResNet-v2) | #24 | Top-1 Accuracy: 77.32Top-5 Accuracy: 91.64… |
| image-classification-on-mini-webvision-1-0 | DivideMix (ResNet-50) | #26 | Top-1 Accuracy: 76.32 ±0.36Top-5 Accuracy: 90.65 ±0.16… |
| image-classification-on-mini-webvision-1-0 | DivideMix (ResNet-18) | #27 | Top-1 Accuracy: 76.08 |
| learning-with-noisy-labels-on-cifar-100n | Divide-Mix | #4 | Accuracy (mean): 71.13 |
| learning-with-noisy-labels-on-cifar-10n | Divide-Mix | #7 | Accuracy (mean): 95.01 |
| learning-with-noisy-labels-on-cifar-10n-1 | Divide-Mix | #14 | Accuracy (mean): 90.18 |
| learning-with-noisy-labels-on-cifar-10n-2 | Divide-Mix | #8 | Accuracy (mean): 90.90 |
| learning-with-noisy-labels-on-cifar-10n-3 | Divide-Mix | #12 | Accuracy (mean): 89.97 |
| learning-with-noisy-labels-on-cifar-10n-worst | Divide-Mix | #6 | Accuracy (mean): 92.56 |