The document proposes constraining the information flow in variational discriminators by adding an information bottleneck. This forces the discriminator to focus only on essential information needed to determine if a sample is real or generated, rather than nonessential details. Experiments show this stabilized training for generative adversarial networks (GANs), improved imitation learning, and helped with inverse reinforcement learning tasks by focusing the discriminator on high-level features.