IEEE

Synthetic Data Generation using Diffusion Models for ML-based Lightpath Quality of Transmission Estimation Under Extreme Data Scarcity

Abstract: Generative diffusion models are gaining attention as a promising solution for synthetic data generation, offering a distinct advantage over traditional statistical methods and basic ...
IEEE

Fed-DPSDG-WGAN: Differentially Private Synthetic Data Generation for Loan Default Prediction via Federated Wasserstein GAN

Abstract: Lenders typically conduct thorough credit checks to mitigate credit default risk before lending money. Proactively predicting loan defaulters has become increasingly important. However, ...