Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Stanford University

Stanford CS236: Deep Generative Models - Lecture 7 - Normalizing Flows

Stanford University via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Dive into the world of normalizing flows in this comprehensive lecture from Stanford University's CS236: Deep Generative Models course. Explore the fundamental concepts and applications of this powerful technique in deep learning, presented by Associate Professor Stefano Ermon. Gain insights into how normalizing flows can be used to transform simple probability distributions into more complex ones, enabling the creation of highly expressive generative models. Follow along with the course materials and deepen your understanding of this advanced topic in artificial intelligence and machine learning.

Syllabus

Stanford CS236: Deep Generative Models I 2023 I Lecture 7 - Normalizing Flows

Taught by

Stanford Online

Reviews

Start your review of Stanford CS236: Deep Generative Models - Lecture 7 - Normalizing Flows

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.