gan_advances

CS-E4070 - Special Course in Machine Learning and Data Science: Advanced Topics in Deep Learning, Aalto University

literature

• https://arxiv.org/abs/1701.07875 - Wasserstein GAN

• https://arxiv.org/abs/1704.00028 - Improved Training of Wasserstein GANs

• https://arxiv.org/abs/1710.10196 - Progressive Growing of GANs for Improved Quality, Stability, and Variation

How to run example:

python WGAN.py --dataset=mnist --dataroot='./data' --outf='results' --niter=100 --cuda