| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| MNIST (test) | Error Rate0.21 | 94 | 3d ago | ||
| MNIST -> USPS (test) | DeepJDOT | Accuracy98.5 | 65 | 2d ago | |
| Digit-Five (test) | LSS | Average Accuracy92.97 | 60 | 3d ago | |
| USPS → MNIST target (test) | Accuracy98.7 | 58 | 2d ago | ||
| USPS -> MNIST | Accuracy99.1 | 38 | 2d ago | ||
| SVHN → MNIST target (test) | Accuracy99.2 | 37 | 2d ago | ||
| MNIST to USPS | DRANet | Accuracy98.2 | 34 | 2d ago | |
| SVHN to MNIST (test) | VMT | Accuracy99.4 | 33 | 3d ago | |
| ColorMNIST | VAE | Adversarial Accuracy100 | 30 | 3d ago | |
| SVHN -> MNIST | distributionally robust learning framework | Accuracy0.944 | 28 | 2d ago | |
| N-MNIST Binary-grid | VGGSNN | Accuracy99.64 | 27 | 3d ago | |
| Biased MNIST unbiased (test) | EnD | Accuracy96.02 | 24 | 3d ago | |
| Colored MNIST foreground color (test) | DebiAN | Unbiased Accuracy86.37 | 24 | 3d ago | |
| MNIST -> SVHN (test) | Accuracy85 | 21 | 3d ago | ||
| MNIST 10-way 10-shot | Oracle-MAML | Accuracy98.51 | 20 | 3d ago | |
| MNIST 10-way 5-shot | Oracle-MAML | Accuracy98.51 | 20 | 3d ago | |
| MNIST 10-way 1-shot | Oracle-MAML | Accuracy97.31 | 20 | 3d ago | |
| DomainNet (test) | Accuracy42.3 | 18 | 3d ago | ||
| RotatedMNIST (test) | FedCCA | Accuracy88.9 | 18 | 3d ago | |
| USPS | Accuracy99.7 | 18 | 3d ago | ||
| SYND → MNIST S45 (target) | B-Net | Target Domain Accuracy94.97 | 14 | 2d ago | |
| SYND → MNIST S20 (target) | B-Net | Accuracy (Target Domain)95.88 | 14 | 2d ago | |
| SYND → MNIST P45 (target) | B-Net | Target Domain Accuracy90.21 | 14 | 2d ago | |
| SYND → MNIST P20 (target) | Accuracy (Target Domain)95.37 | 14 | 2d ago | ||
| MNIST-4 (test) | DIRECT solver | Test Accuracy93.5 | 14 | 3d ago |
