HEAVY-TAILED DIFFUSION MODELS

Abstract

A generative framework enables transformation of a conventional Gaussian diffusion model for modeling heavy-tailed distributions, such as the data distributions typical of scientific applications. In an embodiment, the denoising model predicts short-term or long-term events based on input data (e.g., certain weather or financial variables). In an embodiment, the denoising model generates high resolution data, such as generating local weather forecasts or conditions from certain weather variables for a larger region.

CPC Classifications