Nhiem Ba Nguyen

SafeVAE-GAN: A Novel Re-sampling Approach for Multi-Class Imbalanced Data

SafeVAE-GAN is proposed, a resampling framework that integrates a conditional β-Variational Autoencoder with Wasserstein GAN to generate high-quality minority samples and provides a robust and scalable solution for multi-class imbalanced learning across diverse domains.