Cramer Wold Generator

Cramer-Wold generators are a class of generative models focused on efficiently and stably generating data samples, often within the context of Generative Adversarial Networks (GANs). Current research emphasizes improving the efficiency of these generators, for example, through one-step generation methods and novel architectures incorporating auxiliary branches for better information flow. This work addresses challenges like catastrophic forgetting in incremental learning and aims to improve the quality and stability of generated data, impacting fields requiring high-fidelity data synthesis and continual learning applications.