Margin Adaptation Generative Adversarial Networks

Loss Function

• used mse loss at D/G nets.

Architecture Networks

• Same as MAGAN paper.

DIFFS	MAGAN Paper	ME
Weight initializer	normal dist	HE initializer
z noise (MNIST)	50
z noise (cifar-10)	320

HE Initializer parameters : (factor = 1, FAN_AVG, uniform)

Tensorboard

Elapsed Time : 5h 45m 51s with GTX 1060 6GB x 1

Result

Name	Global Step 25k	Global Step 50k	Global Step 75k
MAGAN

Initial pre-trained margin value : about 3.0585415484215974

To-Do