Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces
Offered By: Generative Memory Lab via YouTube
Course Description
Overview
Explore a groundbreaking approach to generative diffusion models in discrete-state spaces through this 48-minute conference talk by Yen Ting Lin from the Generative Memory Lab. Delve into the innovative concepts presented in the paper "Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces," which introduces a novel framework for applying diffusion models to discrete data. Gain insights into the potential applications and implications of this research for various fields, including natural language processing and image generation.
Syllabus
Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces
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