Physics-Informed Diffusion Models
Published in arXiv (Cornell University) • Mar 21, 2024
NobleIDNI9P34W98R32S23
Authors:,,
Jan-Hendrik Bastek
WaiChing Sun
Dennis M. Kochmann
Abstract
Generative models such as denoising diffusion models are quickly advancing their ability to approximate highly complex data distributions. They are also increasingly leveraged in scientific machine learning, where samples from the implied data distribution are expected to adhere to specific governin...
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