Adversarial learning is a fascinating area of machine learning where two models, a generator and a discriminator, compete against each other to improve their performance. This section provides visualizations that help understand the dynamics of adversarial learning.
Key Visualizations
Generator vs. Discriminator Loss: This visualization shows how the loss functions of the generator and the discriminator evolve over time. The generator tries to fool the discriminator, while the discriminator tries to distinguish between real and generated data.
Adversarial Examples: These visualizations display examples of real data that have been slightly altered to be classified as fake by the discriminator. This helps in understanding the robustness of the discriminator.
Learning Curves: This graph shows the training progress of both the generator and the discriminator. It helps in identifying if either model is overfitting or underfitting.
Images
Here are some images that illustrate adversarial learning:
Generator vs. Discriminator Loss:
Adversarial Example:
Learning Curves:
For more information on adversarial learning, you can visit our Adversarial Learning Tutorial.