Methods › General › Adversarial Training
Adversarial Training
Adversarial Training methods use adversarial techniques to improve generalization (and the quality of representations learnt during training). Adversarial techniques are also sometimes used in the context of generative models with a generator and a discriminator. Below you can find a continuously updating list of adversarial training methods.
Methods
All 14 methods in this collection, most-tagged first. Year is the archive's introduced_year; the archive stores 2000 when it has none, shown here as “–”. Papers counts distinct papers the archive tags with the method. Click a heading to sort.
| GAIL Generative Adversarial Imitation Learning | – | 41 |
| AdvProp | – | 6 |
| SimAug Simulation as Augmentation | – | 4 |
| Accuracy-Robustness Area (ARA) Accuracy-Robustness Area | – | 3 |
| CIDA Continuously Indexed Domain Adaptation | – | 3 |
| DiffAugment | – | 3 |
| Singular Value Clipping | – | 3 |
| Adversarial Soft Advantage Fitting (ASAF) | – | 2 |
| PCIDA Probabilistic Continuously Indexed Domain Adaptation | – | 2 |
| DropAttack | – | 1 |
| Fast_BAT Fast Bi-level Adversarial Training | – | 1 |
| Protagonist Antagonist Induced Regret Environment Design | – | 1 |
| ASAF Adaptive Spline Activation Function | – | 0 |
| Explanation vs Attention Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA | – | 0 |