Artem Ryzhikov

According to our database, Artem Ryzhikov authored at least 12 papers between 2019 and 2025.

Collaborative distances:

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

2025

Learning to Hear Broken Motors: Signature-Guided Data Augmentation for Induction-Motor Diagnostics.

Saraa Ali, Aleksandr Khizhik, Stepan Svirin, Artem Ryzhikov, Denis Derkach

CoRR, June, 2025

Performance Modeling of Data Storage Systems Using Generative Models.

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

IEEE Access, 2025

Unsupervised Learning for Calorimeter Response Correction: A WGAN-Based Method.

Saraa Ali, Artem Ryzhikov, Denis Derkach, Fedor Ratnikov, Vladimir Bocharnikov

Proceedings of the Computational Science and Its Applications - ICCSA 2025 - 25th International Conference, Istanbul, Turkey, June 30, 2025

2024

Intelligent Algorithms For Signature Diagnostics Of Three-Phase Motors.

Stepan Svirin, Artem Ryzhikov, Saraa Ali, Denis Derkach

CoRR, 2024

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.

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

Latent Neural Stochastic Differential Equations for Change Point Detection.

Artem Ryzhikov, Mikhail Hushchyn, Denis Derkach

CoRR, 2022

2021

NFAD: fixing anomaly detection using normalizing flows.

Artem Ryzhikov, Maxim Borisyak, Andrey Ustyuzhanin, Denis Derkach

PeerJ Comput. Sci., 2021

2020

(1 + epsilon)-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets.

Maxim Borisyak, Artem Ryzhikov, Andrey Ustyuzhanin, Denis Derkach, Fedor Ratnikov, Olga Mineeva

J. Mach. Learn. Res., 2020

Variational Dropout Sparsification for Particle Identification speed-up.

Artem Ryzhikov, Denis Derkach, Mikhail Hushchyn

CoRR, 2020

2019

Normalizing flows for deep anomaly detection.

Artem Ryzhikov, Maxim Borisyak, Andrey Ustyuzhanin, Denis Derkach

CoRR, 2019

$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets.

Maxim Borisyak, Artem Ryzhikov, Andrey Ustyuzhanin, Denis Derkach, Fedor Ratnikov, Olga Mineeva

CoRR, 2019