Alexey Boldyrev

According to our database, Alexey Boldyrev authored at least 4 papers between 2020 and 2025.

Collaborative distances:

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

2025

Approach to Finding a Robust Deep Learning Model.

Alexey Boldyrev, Fedor Ratnikov, Andrey Shevelev

CoRR, May, 2025

An Approach to Finding a Robust Deep Learning Model.

Alexey Boldyrev, Fedor Ratnikov, Andrey Shevelev

IEEE Access, 2025

2022

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

Roel Aaij, Marta Adinolfi, Salvatore Aiola, S. Akar, Johannes Albrecht, M. Alexander, S. Amato, Yasmine Amhis, F. Archilli, M. Bala, G. Bassi, L. Bian, M. P. Blago, Thomas Boettcher, Alexey Boldyrev, S. Borghi, A. Brea Rodriguez, Lukas Calefice, M. Calvo Gomez, Daniel Hugo Cámpora Pérez, A. Cardini, Marco Cattaneo, V. Chobanova, G. Ciezarek, Xabier 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, Laurent 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, Federico Lazzari, R. Le Gac, P. Li, J. H. Lopes, M. Lucio Martinez, A. Lupato, Oliver Lupton, X. Lyu, F. Machefert, Olga Madejczyk, S. Malde, J. F. Marchand, Saverio Mariani, Carla Marin Benito, D. Martinez Santos, F. Martinez Vidal, R. Matev, Michal Mazurek, B. Mitreska, Dominik Stefan Mitzel, Michael Joseph 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, Nicola 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, Andrii Usachov, Núria Valls Canudas, R. Vazquez Gomez, Stefania Vecchi, Mika Vesterinen, Xavier Vilasís-Cardona, Dorothea Vom Bruch, Z. Wang, Tomasz Wojton, Mark Whitehead, Mike 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

2020

Using machine learning to speed up new and upgrade detector studies: a calorimeter case.

Fedor Ratnikov, Denis Derkach, Alexey Boldyrev, Andrey Shevelev, P. Fakanov, L. Matyushin

CoRR, 2020