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Regular version of the site
Contacts

125319, Moscow,
3 Kochnovsky Proezd (near metro station 'Aeroport'). 

Phone: +7 (495) 772-95-90 *12332

Email: computerscience@hse.ru

 

Administrations

Dean Ivan Arzhantsev

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
Branching rules related to spherical actions on flag varieties
In press

Roman Avdeev, Petukhov A.

Algebras and Representation Theory. 2019.

Article
Minimax theorems for American options without time-consistency

Belomestny D., Kraetschmer V., Hübner T. et al.

Finance and Stochastics. 2019. Vol. 23. P. 209-238.

Article
Cherenkov detectors fast simulation using neural networks

Kazeev N., Derkach D., Ratnikov F. et al.

Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2019.

Book chapter
Averaging Weights Leads to Wider Optima and Better Generalization

Izmailov P., Garipov T., Подоприхин Д. А. et al.

In bk.: Proceedings of the international conference on Uncertainty in Artificial Intelligence (UAI 2018). 2018. P. 876-885.

Summer school on Machine Learning in High Energy Physics

This is the first announcement of the MLHEP Summer School onMachine Learning for High Energy Physics, to be held atSaint-Petersburg, Russia, just before LHC Physics Conference on  August 27-30, 2015.

The primary goal of this year's MLHEP school will be a focused introduction to modern machine learning techniques that could improve physics performance for variety of HEP problems. School pays attention to student experience, so along with "hands-on" seminars a dedicated data science competition will be organized.
Additionally, the school will include series of talks that show real examples of improvements for particular physics cases due to machine learning techniques.
The school is ideally suited for advanced graduate students and young postdocs.
For further information, including application procedures, pleaserefer to the Summer School website or contact mlhep2015@yandex.ru.