CENG796 DEEP GENERATIVE MODELS
| Course Code: | 5710796 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Computer Engineering |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Assoc.Prof.Dr. RAMAZAN GÖKBERK CİNBİŞ |
| Offered Semester: | Fall Semesters. |
Course Objectives
At the end of the course, the students will be expected to:
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Comprehend a variety of deep generative models.
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Apply deep generative models to several problems.
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Know the open issues in learning deep generative models, and have a grasp of the current research directions.
Course Content
Deep generative modeling with Autoregressive models; Energy-based models; Adversarial models; Variational models.
Course Learning Outcomes
Students who passed the course will be able:
- to understand the theory behind comtemporary deep generative models,
- to have a grasp of the open issues and trends in generative models,
- to have an understanding of the advantages and disadvantages of different types of deep generative model formulations,
- to gain hands-on experience in implementing & realizing generative models.