YoVDO

Generalization in Diffusion Models Arises from Geometry-Adaptive Harmonic Representations

Offered By: Simons Institute via YouTube

Tags

Diffusion Models Courses Machine Learning Courses Neural Networks Courses Computational Geometry Courses Image Generation Courses Generalization Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a comprehensive lecture on the topic of generalization in diffusion models and their connection to geometry-adaptive harmonic representations. Delivered by Zahra Kadkhodaie from New York University, this one-hour and four-minute talk delves into the emerging generalization settings within the field. Gain insights into how diffusion models achieve generalization through their unique ability to adapt to geometric structures, and understand the implications of these findings for the broader field of machine learning and artificial intelligence.

Syllabus

Generalization in Diffusion Models Arises from Geometry-Adaptive Harmonic Rrepresentations


Taught by

Simons Institute

Related Courses

计算几何 | Computational Geometry
Tsinghua University via edX
Geometric Algorithms
EIT Digital via Coursera
Computational Geometry
Saint Petersburg State University via Coursera
Computational Geometry
Indian Institute of Technology Delhi via Swayam
Computational Geometry
NPTEL via YouTube