Academic Catalog


Course Code: 9090714
METU Credit (Theoretical-Laboratory hours/week): 3(3-0)
ECTS Credit: 8.0
Department: Multimedia Informatics
Language of Instruction: English
Level of Study: Graduate
Course Coordinator: Assoc.Prof.Dr. ERDEM AKAGNDZ
Offered Semester: Spring Semesters.

Course Content

This advanced deep learning course offers a comprehensive introduction to the principles and practice of generative modeling. Beginning with a review of the mathematical foundations required for the course, students will gain an understanding of the conventional autoregressive methods used in generative modeling, as well as more contemporary techniques such as deep generative neural models and diffusion models. The course covers all fundamental concepts related to generating media, including latent spaces, latent codes, and encoding. Throughout the course, students will have access to a wide range of resources, including lectures, readings, and hands-on projects. In addition, a thorough review of recent state-of-the-art studies in the field will be provided each year to ensure students are up to date with the latest advances. By the end of the course, students will have gained the skills and knowledge necessary to tackle real-world generative modeling challenges and become proficient practitioners in this field.