Domain Adaptation On Usps To Mnist
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy |
|---|---|
| dranet-disentangling-representation-and | 97.8 |
| discriminative-feature-alignment | 96.6 |
| 190510748 | 95.03 |
| unsupervised-domain-adaptation-using-feature-2 | 98.75 |
| maximum-classifier-discrepancy-for | 95.7 |
| self-ensembling-for-visual-domain-adaptation | 98.07 |
| conditional-adversarial-domain-adaptation | 98.0 |
| discriminative-feature-alignment | 96.2 |
| cluster-alignment-with-a-teacher-for | 96.3 |
| light-weight-calibrator-a-separable-component | 98.3 |
| fact-federated-adversarial-cross-training | 98.6 |
| do-we-really-need-to-access-the-source-data | 98.4 |
| cycle-consistent-conditional-adversarial | 98.3 |
| deepjdot-deep-joint-distribution-optimal | 96.4 |