Dive into a comprehensive explanation of stable diffusion tailored for machine learning engineers in this 38-minute conference talk by Josef Lindman Hörnlund from GAIA. Recorded on October 26, 2022, at Smartr in Gothenburg, the presentation covers the evolution of diffusion models, their original setup, training process, text conditioning, and the concept of latent diffusion. Gain insights into why diffusion models are considered essential and how stable diffusion operates as a latent diffusion model. Explore the timeline of diffusion models and understand their significance in the field of machine learning.
Explaining Stable Diffusion for Machine Learning Engineers
Overview
Syllabus
Explain Stable diffusion like i am a machine learning engineer
Diffusion models is all you need
Diffusion models - timeline
Diffusion models the original setup
Diffusion models - training
Conditioning on text
Stable diffusion is latent diffusion
Latent diffusion- summary
Taught by
GAIA
Related Courses
-
Stable Diffusion
4.0 -
Machine Learning and NLP Basics
-
PyTorch for Deep Learning & Machine Learning – Full Course
-
Introduction to Machine Learning
3.5 -
Stable Diffusion and Friends - High-Resolution Image Synthesis via Two-Stage Generative Models
-
Diffusion Transformer and Rectified Flow in Stable Diffusion 3
