School
Mini-courses
Optimal Transport and Generative Modeling based on Stochastic Processes
Evgeny Burnaev
Skoltech
Posterior sampling and Bayesian bootstrap: sample complexity and regret bounds
Alexey Naumov
HSE University
Tensors and machine learning
Ivan Oseledets
Skoltech
Introduction to diffusion models
Dmitry Vetrov
HSE University
Programme 1-2 November
| 1 November | |
| 09:30 - 10:00 | Registration and welcome |
| 10:00 - 11:15 | Alexey Naumov (HSE University). Posterior sampling and Bayesian bootstrap: sample complexity and regret bounds. Part 1 |
| 11:15 - 11:45 | Coffee break |
| 11:45 - 13:00 | Alexey Naumov & Daniil Tiapkin (HSE University). Posterior sampling and Bayesian bootstrap: sample complexity and regret bounds. Part 2 |
| 13:00 - 14:00 | Free time |
| 14:00 - 15:15 | Ivan Oseledets (Skoltech). Tensors and machine learning. Part 1 |
| 15:15 - 15:35 | Coffee break |
| 15:35 - 16:50 | Ivan Oseledets (Skoltech). Tensors and machine learning. Part 2 |
| 17:00 - 17:30 | Sergey Samsonov (HSE University). Local-Global MCMC kernels: the best of both worlds |
| 17:30 - 18:00 | Andrey Savchenko (HSE University). Computer vision on mobile devices |
| 2 November | |
| 10:00 - 11:15 | Evgeny Burnaev (Skoltech). Optimal Transport and Generative Modeling based on Stochastic Processes. Part 1 |
| 11:15 - 11:45 | Coffee break |
| 11:45 - 13:00 | Evgeny Burnaev (Skoltech). Optimal Transport and Generative Modeling based on Stochastic Processes. Part 2 |
| 13:00 - 14:00 | Free time |
| 14:00 - 15:15 | Dmitry Vetrov (HSE University). Introduction to diffusion models. Part 1 |
| 15:15 - 15:35 | Coffee break |
| 15:35 - 16:50 | Dmitry Vetrov & Dmitry Molchanov (HSE University). Introduction to diffusion models. Part 2 |
| 17:00 - 17:30 | Ivan Kharuk (INR RAS). Machine learning and astrophysics |
| 17:30 - 18:00 | Denis Derkach (HSE University). Machine Learning Challenges in Particle Physics |