2023/2024
Deep Generative Models
Type:
Optional course (faculty)
Delivered by:
Big Data and Information Retrieval School
When:
1, 2 module
Online hours:
52
Open to:
students of one campus
Language:
English
ECTS credits:
6
Contact hours:
10
Course Syllabus
Abstract
Deep generative models are widely used in many areas of applied machine learning. In this course, we dive into modern generative model architectures and algorithms for training them. The lectures will highlight the main approaches proposed by the beginning of 2021, analyze their main advantages and disadvantages. Practical examples aim at generating images, texts and other objects using variational autoencoders (VAE), generative adversarial networks (GAN), autoregressive models, normalizing flows and other approaches. Assignments are motivated by well-known applications of generative models in science and industry. The final assignment is aligned with the everyday activity of ML researchers: reading and reproducing articles.