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Regular version of the site

Centre of Deep Learning and Bayesian Methods

Social networks of the Center
Publications
Book chapter
Revisiting Non-Acyclic GFlowNets in Discrete Environments

Morozov N., Maximov I., Tiapkin D. et al.

In bk.: Volume 267: International Conference on Machine Learning, 13-19 July 2025, Vancouver Convention Center, Vancouver, Canada. Vol. 267. 2025. P. 44887-44910.

Book chapter
TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings

Shabalin A., Meshchaninov V., Chimbulatov E. et al.

In bk.: Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence. Vol. 39. Iss. 23. United States of America; Washington: AAAI Press, 2025. Ch. 110. P. 25110-25118.

Book chapter
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization

Timofei Gritsaev, Morozov N., Samsonov S. et al.

In bk.: Proceedings of the 13th International Conference on Learning Representations (ICLR 2025). ICLR, 2025. P. 95626-95646.

About the Centre

The Centre conducts research at the intersection of two actively developing areas of data analysis: deep learning and Bayesian methods of machine learning methods. Deep learning is a section that involves building very complex models (neural networks) to solve problems such as classifying images or music, transferring an art style from picture to photograph, predicting the next words in a text. Within the framework of the Bayesian approach, probabilistic models based on the apparatus of probability theory and mathematical statistics are considered for solving such problems.

The Centre was created on the basis of the Dmitry Vetrov's Bayesian Methods Research Group.


Illustration for news: Scientific Expedition to Hainan: HSE Scientists Organise Conference on Statistical AI in China

Scientific Expedition to Hainan: HSE Scientists Organise Conference on Statistical AI in China

The Statistical AI Conference was held in Sanya, Hainan Island, China, from 24 to 28 August 2026. The international event brought together leading experts in statistics, machine learning, and applied AI. Alexey Naumov, Director of the AI and Digital Science Institute at the HSE Faculty of Computer Science, and Sergey Samsonov, Head of the International Laboratory of Stochastic Algorithms and High-Dimensional Inference, were among the conference organisers.

Illustration for news: Speed, Precision, and Self-Correction: HSE Faculty of Computer Science Researchers at ICML-2026

Speed, Precision, and Self-Correction: HSE Faculty of Computer Science Researchers at ICML-2026

Researchers from the HSE Faculty of Computer Science (FCS) presented their work at theInternational Conference on Machine Learning (ICML 2026) in Seoul, South Korea, one of the leading scientific events in the field. Several projects by the faculty’s researchers received the prestigious Spotlight distinction.