Xueping Zhao

Neural Stability Enhancement Through Dynamic Lipschitz Constraints in Generative Adversarial Networks.

This work challenges the conventional fixed-constraint paradigm by formalizing how the effective constraint strength and a bound-implied Lipschitz constant target can depend on architecture and training state and introduces ALC, a modular mechanism that adjusts the Lipschitz constant target rather than introducing anot...