no code implementations • 22 Sep 2023 • Lucio Anderlini, Matteo Barbetti, Simone Capelli, Gloria Corti, Adam Davis, Denis Derkach, Nikita Kazeev, Artem Maevskiy, Maurizio Martinelli, Sergei Mokonenko, Benedetto Gianluca Siddi, Zehua Xu
In this context, we propose Lamarr, a Gaudi-based framework designed to offer the fastest solution for the simulation of the LHCb detector.
no code implementations • 15 Jan 2023 • Sergei Popov, Mikhail Lazarev, Vladislav Belavin, Denis Derkach, Andrey Ustyuzhanin
There are many problems in physics, biology, and other natural sciences in which symbolic regression can provide valuable insights and discover new laws of nature.
2 code implementations • 15 Sep 2022 • Mariia Demianenko, Konstantin Malanchev, Ekaterina Samorodova, Mikhail Sysak, Aleksandr Shiriaev, Denis Derkach, Mikhail Hushchyn
Modern-day time-domain photometric surveys collect a lot of observations of various astronomical objects and the coming era of large-scale surveys will provide even more information on their properties.
1 code implementation • 22 Aug 2022 • Artem Ryzhikov, Mikhail Hushchyn, Denis Derkach
Change point detection algorithms are aimed to locating abrupt changes in the time series behaviour of a process.
1 code implementation • 27 Jun 2022 • Mariia Demianenko, Ekaterina Samorodova, Mikhail Sysak, Aleksandr Shiriaev, Konstantin Malanchev, Denis Derkach, Mikhail Hushchyn
Normalizing Flows exceeds Gaussian processes in terms of approximation quality as well.
no code implementations • 21 Apr 2022 • Lucio Anderlini, Matteo Barbetti, Denis Derkach, Nikita Kazeev, Artem Maevskiy, Sergei Mokhnenko
The increasing luminosities of future data taking at Large Hadron Collider and next generation collider experiments require an unprecedented amount of simulated events to be produced.
1 code implementation • 3 Oct 2020 • Mikhail Hushchyn, Kenenbek Arzymatov, Denis Derkach
Moments when a time series changes its behaviour are called change points.
1 code implementation • 18 Jun 2020 • Stanislav Dobryakov, Konstantin Malanchev, Denis Derkach, Mikhail Hushchyn
We propose a novel approach for a machine-learning-based detection of the type Ia supernovae using photometric information.
1 code implementation • 21 Jan 2020 • Artem Ryzhikov, Denis Derkach, Mikhail Hushchyn
Accurate particle identification (PID) is one of the most important aspects of the LHCb experiment.
1 code implementation • 19 Dec 2019 • Artem Ryzhikov, Maxim Borisyak, Andrey Ustyuzhanin, Denis Derkach
Most of the conventional approaches to anomaly detection, such as one-class SVM and Robust Auto-Encoder, are one-class classification methods, i. e. focus on separating normal data from the rest of the space.
1 code implementation • 14 Jun 2019 • Maxim Borisyak, Artem Ryzhikov, Andrey Ustyuzhanin, Denis Derkach, Fedor Ratnikov, Olga Mineeva
We explore a novel method that gives a trade-off possibility between one-class and two-class approaches, and leads to a better performance on anomaly detection problems with small or non-representative anomalous samples.
no code implementations • 28 May 2019 • Artem Maevskiy, Denis Derkach, Nikita Kazeev, Andrey Ustyuzhanin, Maksim Artemev, Lucio Anderlini
The increasing luminosities of future Large Hadron Collider runs and next generation of collider experiments will require an unprecedented amount of simulated events to be produced.
no code implementations • 28 Mar 2019 • Denis Derkach, Nikita Kazeev, Fedor Ratnikov, Andrey Ustyuzhanin, Alexandra Volokhova
We propose a way to simulate Cherenkov detector response using a generative adversarial neural network to bypass low-level details.
no code implementations • 25 Sep 2017 • Maxim Borisyak, Fedor Ratnikov, Denis Derkach, Andrey Ustyuzhanin
Daily operation of a large-scale experiment is a challenging task, particularly from perspectives of routine monitoring of quality for data being taken.
no code implementations • 25 Sep 2017 • Maxim Borisyak, Andrey Ustyuzhanin, Denis Derkach, Mikhail Belous
High-energy physics experiments rely on reconstruction of the trajectories of particles produced at the interaction point.
no code implementations • 24 May 2017 • Tatiana Likhomanenko, Denis Derkach, Alex Rogozhnikov
The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of $B$ mesons in any proton-proton experiment.