Fedor Ratnikov

20 papers Journal 19Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	An Approach to Finding a Robust Deep Learning Model. IEEE Access Alexey Boldyrev, Fedor Ratnikov, Andrey Shevelev
2025	J	`jnl`	Approach to Finding a Robust Deep Learning Model. CoRR Alexey Boldyrev, Fedor Ratnikov, Andrey Shevelev
2025	J	`jnl`	Dynamic Functional Connectivity Features for Brain State Classification: Insights from the Human Connectome Project. CoRR Valeriya Kirova, Dzerassa Kadieva, Daniil Vlasenko, Isak B. Blank, Fedor Ratnikov
2025	J	`jnl`	Optimisation of the Accelerator Control by Reinforcement Learning: A Simulation-Based Approach. CoRR Anwar Ibrahim, Denis Derkach, Alexey Petrenko, Fedor Ratnikov, Maxim Kaledin
2025	J	`jnl`	Reinforcement Learning for Accelerator Beamline Control: a simulation-based approach. CoRR Anwar Ibrahim, Alexey Petrenko, Maxim Kaledin, Ehab Suleiman, Fedor Ratnikov, Denis Derkach
2025	—	`conf`	Unsupervised Learning for Calorimeter Response Correction: A WGAN-Based Method. ICCSA (3) Saraa Ali, Artem Ryzhikov, Denis Derkach, Fedor Ratnikov, Vladimir Bocharnikov
2024	J	`jnl`	Soft Margin Spectral Normalization for GANs. Comput. Softw. Big Sci. Alexander Rogachev, Fedor Ratnikov
2023	J	`jnl`	What Machine Learning Can Do for Focusing Aerogel Detectors. CoRR Foma Shipilov, Alexander Barnyakov, Vladimir Bobrovnikov, Sergey Kononov, Fedor Ratnikov
2022	J	`jnl`	A Comparison of CPU and GPU Implementations for the LHCb Experiment Run 3 Trigger. Comput. Softw. Big Sci. 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, Sergey 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, Anna 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, Rosen Matev, Michal Mazurek, Biljana 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, Miguel Ramos Pernas, M. S. Rangel, Fedor Ratnikov, Gerhard 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, Holger 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
2022	J	`jnl`	Energy reconstruction for large liquid scintillator detectors with machine learning techniques: aggregated features approach. CoRR Arsenii Gavrikov, Yury Malyshkin, Fedor Ratnikov
2020	J	`jnl`	(1 + epsilon)-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets. J. Mach. Learn. Res. Maxim Borisyak, Artem Ryzhikov, Andrey Ustyuzhanin, Denis Derkach, Fedor Ratnikov, Olga Mineeva
2020	J	`jnl`	Generative Adversarial Networks for LHCb Fast Simulation. CoRR Fedor Ratnikov
2020	J	`jnl`	Using Machine Learning to Speed Up and Improve Calorimeter R&D. CoRR Fedor Ratnikov
2020	J	`jnl`	Using machine learning to speed up new and upgrade detector studies: a calorimeter case. CoRR Fedor Ratnikov, Denis Derkach, Alexey Boldyrev, Andrey Shevelev, P. Fakanov, L. Matyushin
2019	J	`jnl`	$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets. CoRR Maxim Borisyak, Artem Ryzhikov, Andrey Ustyuzhanin, Denis Derkach, Fedor Ratnikov, Olga Mineeva
2019	J	`jnl`	Cherenkov Detectors Fast Simulation Using Neural Networks. CoRR Denis Derkach, Nikita Kazeev, Fedor Ratnikov, Andrey Ustyuzhanin, Alexandra Volokhova
2018	J	`jnl`	Generative Models for Fast Calorimeter Simulation.LHCb case. CoRR Viktoria Chekalina, Elena Orlova, Fedor Ratnikov, Dmitry Ulyanov, Andrey Ustyuzhanin, Egor Zakharov
2017	J	`jnl`	Deep learning for inferring cause of data anomalies. CoRR V. Azzolini, Maxim Borisyak, Gianluca Cerminara, Denis Derkach, Giovanni Franzoni, F. De Guio, O. Koval, Maurizio Pierini, Adrian Alan Pol, Fedor Ratnikov, Filip Siroky, Andrey Ustyuzhanin, Jean-Roch Vlimant
2017	J	`jnl`	Towards automation of data quality system for CERN CMS experiment. CoRR Maxim Borisyak, Fedor Ratnikov, Denis Derkach, Andrey Ustyuzhanin
2003	J	`jnl`	Management of Grid Jobs and Information within SAMGrid CoRR A. Baranovski, Gabriele Garzoglio, Arthur Kreymer, Lee Lueking, Stefan Stonjek, Igor Terekhov, Frank Würthwein, Alain Roy, P. Mhashikar, V. Murthi, Todd Tannenbaum, Rod Walker, Fedor Ratnikov, T. Rockwell