Materials scientists from The Grainger College of Engineering have provided the first quantitative explanation for a phenomenon first observed in iron in the 1970s.

Abstract: The rapid growth of generative models has led to a new direction in steganography called generative steganography (GS). It allows message-to-image generation without the need for a carrier ...

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

Abstract: Recently, diffusion models as a hot paradigm have shown considerable superiority in image restoration with an unsupervised manner. However, they require iterative refinement from isotropic ...