Generative Discrimination
Minibatch Discrimination
Introduced by Salimans et al. in Improved Techniques for Training GANsMinibatch Discrimination is a discriminative technique for generative adversarial networks where we discriminate between whole minibatches of samples rather than between individual samples. This is intended to avoid collapse of the generator.
Source: Improved Techniques for Training GANs
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Generation | 2 | 33.33% |
| Aspect-Based Sentiment Analysis (ABSA) | 1 | 16.67% |
| Sentiment Analysis | 1 | 16.67% |
| Conditional Image Generation | 1 | 16.67% |
| Semi-Supervised Image Classification | 1 | 16.67% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
