Mikhail Hushchyn

According to our database, Mikhail Hushchyn authored at least 16 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

The Tracking Machine Learning Challenge: Throughput Phase.

Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, Steven Farrell, Cécile Germain, Vladimir Vava Gligorov, Tobias Golling, Sergey Gorbunov, Heather M. Gray, Isabelle Guyon, Mikhail Hushchyn, Vincenzo Innocente, Moritz Kiehn, Marcel Kunze, Edward Moyse, David Rousseau, Andreas Salzburger, Andrey Ustyuzhanin, Jean-Roch Vlimant

Comput. Softw. Big Sci., December, 2023

Performance Modeling of Data Storage Systems using Generative Models.

Abdalaziz Rashid Al-Maeeni, Aziz Temirkhanov, Artem Ryzhikov, Mikhail Hushchyn

CoRR, 2023

Latent Stochastic Differential Equations for Change Point Detection.

Artem Ryzhikov, Mikhail Hushchyn, Denis Derkach

IEEE Access, 2023

2022

A Comparison of CPU and GPU Implementations for the LHCb Experiment Run 3 Trigger.

R. Aaij, Marta Adinolfi, Salvatore Aiola, S. Akar, J. Albrecht, M. Alexander, S. Amato, Yasmine Amhis, F. Archilli, M. Bala, G. Bassi, L. Bian, M. P. Blago, T. Boettcher, A. Boldyrev, S. Borghi, A. Brea Rodriguez, Lukas Calefice, M. Calvo Gomez, Daniel Hugo Cámpora Pérez, A. Cardini, Marco Cattaneo, V. Chobanova, G. Ciezarek, X. Cid Vidal, J. L. Cobbledick, J. A. B. Coelho, Tommaso Colombo, A. Contu, Benjamin Couturier, Daniel C. Craik, R. Currie, P. d'Argent, Michel De Cian, Denis Derkach, F. Dordei, Marco Dorigo, L. Dufour, Paolo Durante, A. Dziurda, A. Dzyuba, S. Easo, S. Esen, Placido Fernandez Declara, S. Filippov, Conor Fitzpatrick, M. Frank, Paolo Gandini, Vladimir V. Gligorov, Elisabet Golobardes, G. Graziani, L. Grillo, P. A. Günther, S. Hansmann-Menzemer, Arthur M. Hennequin, Louis Henry, D. Hill, S. E. Hollitt, J. Hu, W. Hulsbergen, R. J. Hunter, Mikhail Hushchyn, Brij Kishor Jashal, Christopher Robert Jones, S. Klaver, Konrad Klimaszewski, R. Kopecna, Wojciech Krzemien, Marcin Kucharczyk, R. Lane, F. Lazzari, R. Le Gac, P. Li, J. H. Lopes, M. Lucio Martinez, A. Lupato, Oliver Lupton, X. Lyu, F. Machefert, O. Madejczyk, S. Malde, J. F. Marchand, S. Mariani, Carla Marin Benito, D. Martinez Santos, F. Martinez Vidal, R. Matev, Michal Mazurek, B. Mitreska, D. S. Mitzel, M. J. Morello, H. Mu, P. Muzzetto, P. Naik, Matthew D. Needham, N. Neri, Niko Neufeld, N. S. Nolte, Daniel O'Hanlon, A. Oyanguren Campos, M. Pepe Altarelli, S. Petrucci, Marco Petruzzo, L. Pica, Flavio Pisani, A. Piucci, Francesco Polci, A. Poluektov, E. Polycarpo, C. Prouve, Giovanni Punzi, Renato Quagliani, R. I. Rabadan Trejo, M. Ramos Pernas, M. S. Rangel, Fedor Ratnikov, G. Raven, F. Reiss, V. Renaudin, P. Robbe, Artem Ryzhikov, Marco Santimaria, M. Saur, Manuel T. Schiller, Rainer Schwemmer, Barbara Sciascia, A. Solomin, F. Suljik, N. Skidmore, Michael D. Sokoloff, P. Spradlin, M. Stahl, S. Stahl, H. Stevens, L. Sun, A. Szabelski, Tomasz Szumlak, M. Szymanski, D. Y. Tou, Giulia Tuci, A. Usachov, Núria Valls Canudas, R. Vazquez Gomez, Stefania Vecchi, Mika Vesterinen, Xavier Vilasís-Cardona, Dorothea Vom Bruch, Z. Wang, Tomasz Wojton, Mark Whitehead, M. Williams, Mariusz Witek, Y. Xie, A. Xu, H. Yin, Milosz Zdybal, O. Zenaiev, D. Zhang, L. Zhang, X. Zhu, The LHCb Collaboration

Comput. Softw. Big Sci., 2022

Toward an understanding of the properties of neural network approaches for supernovae light curve approximation.

Mariia Demianenko, Konstantin L. Malanchev, Ekaterina Samorodova, Mikhail Sysak, Aleksandr Shiriaev, Denis Derkach, Mikhail Hushchyn

CoRR, 2022

Latent Neural Stochastic Differential Equations for Change Point Detection.

Artem Ryzhikov, Mikhail Hushchyn, Denis Derkach

CoRR, 2022

Supernova Light Curves Approximation based on Neural Network Models.

Mariia Demianenko, Ekaterina Samorodova, Mikhail Sysak, Aleksandr Shiriaev, Konstantin L. Malanchev, Denis Derkach, Mikhail Hushchyn

CoRR, 2022

2021

Generalization of change-point detection in time series data based on direct density ratio estimation.

Mikhail Hushchyn, Andrey Ustyuzhanin

J. Comput. Sci., 2021

Online detection of failures generated by storage simulator.

Kenenbek Arzymatov, Mikhail Hushchyn, Andrey A. Sapronov, Vladislav Belavin, Leonid Gremyachikh, Maksim Karpov, Andrey Ustyuzhanin

CoRR, 2021

Photometric data-driven classification of Type Ia supernovae in the open Supernova Catalog.

Stanislav Dobryakov, Konstantin L. Malanchev, Denis Derkach, Mikhail Hushchyn

Astron. Comput., 2021

2020

Online Neural Networks for Change-Point Detection.

Mikhail Hushchyn, Kenenbek Arzymatov, Denis Derkach

CoRR, 2020

Variational Dropout Sparsification for Particle Identification speed-up.

Artem Ryzhikov, Denis Derkach, Mikhail Hushchyn

CoRR, 2020

2018

TrackML: A High Energy Physics Particle Tracking Challenge.

Paolo Calafiura, Steven Farrell, Heather M. Gray, Jean-Roch Vlimant, Vincenzo Innocente, Andreas Salzburger, Sabrina Amrouche, Tobias Golling, Moritz Kiehn, Victor Estrade, Cécile Germain, Isabelle Guyon, Ed Moyse, David Rousseau, Yetkin Yilmaz, Vladimir Vava Gligorov, Mikhail Hushchyn, Andrey Ustyuzhanin

Proceedings of the 14th IEEE International Conference on e-Science, 2018

2017

GRID Storage Optimization in Transparent and User-Friendly Way for LHCb Datasets.

Mikhail Hushchyn, Andrey Ustyuzhanin, Philippe Charpentier, Christophe Haen

CoRR, 2017

2015

Disk storage management for LHCb based on Data Popularity estimator.

Mikhail Hushchyn, Philippe Charpentier, Andrey Ustyuzhanin

CoRR, 2015

Distributed Data Replication and Access Optimization for LHCb Storage System.

Mikhail Hushchyn, Philippe Charpentier, Andrey Ustyuzhanin

Proceedings of the KDIR 2015, 2015