Federated Learning (FL) has emerged as a solution for distributed systems that allow clients
to train models on their data and only share models instead of local data. Generative Models …

Deep generative modeling has emerged as a powerful tool for synthesizing realistic medical
images, driving advances in medical image analysis, disease diagnosis, and treatment …

Generative diffusion models (GDMs) have emerged as potent tools for generating high-
quality, creative content across various media, including audio, images, videos, and 3-D …

Realistic synthetic tabular data generation encounters significant challenges in preserving
privacy, especially when dealing with sensitive information in domains like finance and …

We introduce FedDM, a novel training framework designed for the federated training of
diffusion models. Our theoretical analysis establishes the convergence of diffusion models …

The Satellite-Terrestrial Integrated Network (STIN) is an emerging paradigm offering
seamless network services across geographical boundaries, yet it faces significant security …

The increasing demand for privacy-preserving data analytics in finance necessitates
solutions for synthetic data generation that rigorously uphold privacy standards. We …

Generative Artificial Intelligence (GAI) shows remarkable productivity and creativity in Mobile
Edge Networks, such as the metaverse and the Industrial Internet of Things. Federated …