We reinterpreting the variational inference in a new perspective. Via this way, we can easily prove that EM algorithm, VAE, GAN, AAE, ALI(BiGAN) are all special cases of variational inference. The proof also reveals the loss of standard GAN is incomplete and it explains why we need to train GAN cautiously. From that, we find out a regularization term to improve stability of GAN training.

翻译：我们从新的角度重新解释变式推论。 这样, 我们就可以很容易地证明 EM 算法, VAE, GAN, AAE, Alli( BIGAN ) 都是变式推论的特例。 证据还揭示了标准 GAN 的丢失是不完整的, 这解释了为什么我们需要谨慎地培训 GAN 。 从这个角度, 我们发现一个正规化的术语来提高 GAN 培训的稳定性 。