Diffusion Models as Plug-and-Play Priors
Offered By: Generative Memory Lab via YouTube
Course Description
Overview
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.
Syllabus
Diffusion models as plug-and-play priors
Taught by
Generative Memory Lab
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent