Adversarial Training of Conditional Normalizing Flows to Mitigate Mode Collapse

The core message of this work is to propose an adversarially trained conditional normalizing flow (AdvNF) model that can effectively model complex multi-modal distributions, such as those encountered in physical systems, and overcome the problem of mode collapse that plagues standard conditional normalizing flow models.