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Contacts

109028, Moscow,
11, Pokrovsky boulevard

Phone: +7 (495) 531-00-00 *27254

Email: computerscience@hse.ru

 

Administrations
First Deputy Dean Tamara Voznesenskaya
Deputy Dean for Research and International Relations Sergei Obiedkov
Deputy Dean for Methodical and Educational Work Ilya Samonenko
Deputy Dean for Development, Finance and Administration Irina Plisetskaya
Events
Article
Convergence rates for empirical barycenters in metric spaces: curvature, convexity and extendable geodesics
In press

Ahidar-Coutrix A., Le Gouic T., Paris Q.

Probability Theory and Related Fields. 2020.

Article
Machine Learning on data with sPlot background subtraction

M. Borisyak, N. Kazeev.

Journal of Instrumentation. 2019. Vol. 14. No. 08. P. 1-8.

Book chapter
Subspace Inference for Bayesian Deep Learning

Vetrov D., Izmailov P., Maddox W. J. et al.

In bk.: Proceedings of the 35th Uncertainty in Artificial Intelligence Conference (UAI-2019). 2019. P. 1-11.

Book chapter
The logic of action lattices is undecidable

Kuznetsov S.

In bk.: 34th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS 2019). IEEE, 2019. Ch. 36. P. 1-9.

Tag "Centre of Deep Learning and Bayesian Methods" – News

The leading researcher at Samsung-HSE Laboratory became the winner of the Moscow Government Young Scientist Prize for 2019

The leading researcher at Samsung-HSE Laboratory became the winner of the Moscow Government Young Scientist Prize for 2019

The third Summer School on Deep Learning and Bayesian Methods was held in Moscow

The third Summer School on Deep Learning and Bayesian Methods was held in Moscow

The faculty presented the results of their research at the largest international machine learning conference NeurIPS

The faculty presented the results of their research at the largest international machine learning conference NeurIPS
Researchers of the Faculty of Computer Science presented their papers at the annual conference of Neural Information Processing Systems (NeurIPS), which was held from 2 to 8 December 2018 in Montreal, Canada.

DeepBayes 2018: More Bayesian Methods in Deep Learning

DeepBayes 2018: More Bayesian Methods in Deep Learning
The second Summer School on Deep Learning and Bayesian Methods was held in Moscow from August 27 to September 1, this year in English. During 6 days participants were studying and implementing Bayesian methods in neural networks, exchanging their experience and discussing research ideas.

Mini-workshop Stochastic Processes and Probabilistic Models in Machine Learning

Mini-workshop Stochastic Processes and Probabilistic Models in Machine Learning
On September 12 and 13, a mini-workshop "Stochastic processes and probabilistic models in machine learning" was held at the faculty. Four invited foreign specialists gave lectures about the application of parametric and nonparametric probabilistic methods in machine learning, and representatives of Russian scientific groups told about particular projects where these approaches are used.
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