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Contacts

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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
Article
Infinite transitivity, finite generation, and Demazure roots

Arzhantsev I., Kuyumzhiyan K., Zaidenberg M.

Advances in Mathematics. 2019. Vol. 351. P. 1-32.

Article
Bias in False Discovery Rate Estimation in Mass-Spectrometry-Based Peptide Identification

Sulimov P., Voronkova A., Danilova Y. et al.

Journal of Proteome Research. 2019. Vol. 18. No. 5. P. 2354-2358.

Article
Compression of recurrent neural networks for efficient language modeling

Grachev A., Ignatov D. I., Savchenko A.

Applied Soft Computing Journal. 2019. Vol. 79. P. 354-362.

Book chapter
Numerical Pattern Mining Through Compression

Makhalova T., Kuznetsov S., Napoli A.

In bk.: 2019 Data Compression Conference Proceedings. IEEE, 2019.

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

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.

Bayesian Methods in Deep Learning Summer School in Moscow

Bayesian Methods in Deep Learning Summer School in Moscow
Bayesian Methods in Deep Learning Summer School was held in Moscow fron 26 to 30 August. During these five days 96 participants from 8 countries listened to lectures about Bayesian methods in deep learning and trained neural networks.
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