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Critical Windows: Non-Asymptotic Theory for Feature Emergence in Diffusion Models

Offered By: Generative Memory Lab via YouTube

Tags

Diffusion Models Courses Artificial Intelligence Courses Machine Learning Courses Deep Learning Courses Generative Models Courses

Course Description

Overview

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Explore the groundbreaking research presented by Marvin Li on non-asymptotic theory for feature emergence in diffusion models. Delve into the concept of critical windows and their significance in understanding the behavior of diffusion models. Gain insights into the theoretical foundations and practical implications of this innovative approach, which challenges traditional asymptotic analyses. Learn how this research contributes to advancing our understanding of feature emergence in machine learning and artificial intelligence.

Syllabus

Critical windows: non-asymptotic theory for feature emergence in diffusion models


Taught by

Generative Memory Lab

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