Code for the paper: Adversarial Inference by Matching priors and conditionals
MNIST
python main.py --dataset 'mnist' --root 'your/root/directory' --epoch 100 --batch_size 64 --beta1 0.5
Mixed Gaussian
python main.py --dataset 'mixed-Gaussian' --root 'your/root/directory' --epoch 200 --batch_size 100 --beta1 0.8
dcGAN structure LAI
python main.py --model_name 'dcLAI' --dataset 'svhn' --root 'your/root/directory' --epoch 20 --batch_size 128 --beta1 0.5 --z_dim 100