Deep Generative Models

This repository contains materials for the Deep Generative Models course taught at the Faculty of Computer Science of HSE University and Yandex School of Data Analysis.

Lectures: Artem Ryzhikov

Seminars: Aleksandr Khizhik

Assistants: Mariia Rubanenko

Grading

The final grade is calculated using the following formula:

$$ O_{\text{final}} = 8 \cdot 0.08 \cdot O_{\text{homework}} + 0.16 \cdot O_{\text{project}} + 0.2 \cdot O_{\text{exam}} $$

Where:

• Homework consists of 8 assignments with applied problems. Deadlines are strict (2 weeks) with no extensions allowed.
• Bonus points can be earned in the homework section by completing additional tasks.
• Project involves implementing and publishing an article at one of the recognized conferences.
• Exam is conducted orally, using an open list of questions, with no additional preparation time provided.

Make sure to meet the deadlines and requirements for each component to achieve the best possible grade.