MAD-GAN

TensorFlow implementation of Multi-Agent Diverse Generative Adversarial Network (MAD-GAN) In three different datasets:

• A distribution of 1D GMM having five mixture components with modes at 10, 20, 60, 80 and 110, and standard deviations of 3, 3, 2, 2 and 1, respectively.
• A distribution of 2D GMM having six mixture components with modes at circumference of a cricle with radius of 5
• MNIST dataset

Results

Resources

• Ghosh, Arnab, et al. "Multi-agent diverse generative adversarial networks." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018.