Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics ...

Diffusion models are generative models (a type of AI model which learns to model data distribution from the input). Once learned, these models can generate new data samples similar to those which ...

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics ...

Diffusion probabilistic models (DPMs) have achieved impressive success in high-resolution image synthesis, especially in recent large-scale text-to-image generation applications. An essential ...

AMD and Stability AI have launched the first Stable Diffusion 3.0 Medium model optimized for BF16 and XDNA 2 NPUs, enabling high-quality, offline image generation on Ryzen AI laptops.

AI image generators like Stable Diffusion and DALL-E amplify bias in gender and race, despite efforts to detoxify the data fueling these results. By Nitasha Tiku, Kevin Schaul and Szu Yu Chen Nov ...

New research shows that threat actors can easily implant backdoors in diffusion models used in DALL-E 2 and open-source text-to-image models.

Jonathan Fintzi, Xiang Cui, Jon Wakefield, Vladimir N. Minin, Efficient Data Augmentation for Fitting Stochastic Epidemic Models to Prevalence Data, Journal of Computational and Graphical Statistics, ...

The term data augmentation refers to methods for constructing iterative optimization or sampling algorithms via the introduction of unobserved data or latent variables. For deterministic algorithms, ...

Stability says that the Stable Diffusion 3.5 models should generate more “diverse” outputs — that is to say, images depicting people with different skin tones and features — without the ...