Researchers combined two types of generative AI models, an autoregressive model and a diffusion model, to create a tool that leverages the best of each model to rapidly generate high-quality images.

Autoregressive models are a statistical technique used to predict future values in a sequence based on its past values. It is essentially a fancy way of saying that it uses the past to predict the ...

Autoregressive model and diffusion model (IMAGE) Massachusetts Institute of Technology Caption Researchers combined two types of generative AI models, an autoregressive model and a diffusion model, to ...

Spatial econometrics addresses the challenges posed by spatially correlated data, enabling researchers to understand and quantify how economic phenomena in one location can influence those in ...

This article introduces a new model called the buffered autoregressive model with generalized autoregressive conditional heteroscedasticity (BAR-GARCH). The proposed model, as an extension of the BAR ...

Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Meta is continuing to push forward with its research into new forms of ...

So a diffusion model, denoising data, peak signal-to-noise-ratio, RL-agent, autoregressive model, and thermodynamics walk into a bar ... And now we can play the 1993 cult-classic first-person shooter, ...

Chinese company Zhipu AI has trained image generation model entirely on Huawei processors, demonstrating that Chinese firms can build competitive AI systems without access to advanced Western chips.

Researchers developed a hybrid AI approach that can generate realistic images with the same or better quality than state-of-the-art diffusion models, but that runs about nine times faster and uses ...