HSE University and Yandex invite you to the joint third autumn school on generative models aimed at young undergraduate/graduate students planning to develop a research career. This intense four-day workshop will consist of 3 interdisciplinary mini-courses, a list of invited talks, and a lively discussions. Key topics of this school are:
- Generative models basics
- Advanced generative models
- Efficient sampling for generative models
Due to the pandemic, the school will run in the mixed format: in addition to a zoom meeting room, a physical room is booked to allow participants to follow the event from the YSDA campus.
The school is organised by three HSE laboratories:
- LAMBDA (Laboratory of Methods for Big Data Analysis)
- DeepBayes (Centre of Deep Learning and Bayesian Methods)
- HDI Lab (International laboratory of stochastic algorithms and high-dimensional inference)
Yandex is an industry partner of the school.
Pre-requisites:
- Statistics 101
- machine learning 101
- neural networks basic level
- PyTorch
Mini-courses:
- Generative models by Denis Derkach (HSE University)
- Diffusion Generative Models by Dmitry Vetrov (HSE University)
- Efficient Sampling Techniques by Alexey Naumov (HSE University)
Invited talks (TBC):
- Dmitry Vetrov (HSE)
- Alexey Naumov (HSE)
- Denis Derkach (HSE)
- Sergey Shirobokov (ICL, Twitter)
- Maxim Panov (Skoltech)
- Mikhail Burtsev (MIPT)
- Mikhail Lazarev (HSE)
- Nikita Kazeev (HSE)
Registration:
Please register for the school using this form.
School materials:
Please note that most of the materials (slides) will be in English, although the primary language of the school will be Russian. All materials of the school are available via this page timetable. It contains slides of the lectures and talks. All seminar materials are available via the github repository.
This school is supported by the RSF grant N19-71-30020, "Applications of probabilistic artificial neural generative models to the development of digital twin technology for Non-linear stochastic systems."
