Single Source Domain Generalization On Digits
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy |
|---|---|
| center-aware-adversarial-augmentation-for | 80.56 |
| learning-to-diversify-for-single-domain | 74.46 |
| crafting-distribution-shifts-for-validation | 82.61 |
| adversarial-bayesian-augmentation-for-single | 76.72 |
| meta-causal-learning-for-single-domain | 78.82 |
| meta-convolutional-neural-networks-for-single | 78.76 |
| progressive-random-convolutions-for-single | 81.35 |