Explore a comprehensive presentation by Alexandros Graikos on his paper "Diffusion models as plug-and-play priors," delving into the innovative application of diffusion models as versatile priors in various machine learning tasks. Gain insights into the theoretical foundations and practical implications of this approach, which has the potential to revolutionize generative modeling and image processing techniques. Learn how these models can be seamlessly integrated into existing frameworks, offering enhanced performance and flexibility across a wide range of applications.
Overview
Syllabus
Diffusion models as plug-and-play priors
Taught by
Generative Memory Lab
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