Denis Derkach - RankMe

37 papers A 1Journal 34Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning to hear broken motors: Signature-guided data augmentation for induction motor diagnostics. Eng. Appl. Artif. Intell. Saraa Ali, Aleksandr Khizhik, Stepan Svirin, Artem Ryzhikov, Denis Derkach
2026	J	`jnl`	Online Neural Networks for Change-Point Detection. Mach. Learn. Mikhail Hushchyn, Kenenbek Arzymatov, Denis Derkach
2026	J	`jnl`	The Ratan Active Region Patches (RARPs) database: A new database of solar active region radio signatures from the RATAN-600 telescope. Astron. Comput. Maxim Korelov, Irina Knyazeva, Evgenii Kurochkin, Nikolay Grigorevich Makarenko, Denis Derkach
2025	J	`jnl`	Application of Physics-Informed Neural Networks for Solving the Inverse Advection-Diffusion Problem to Localize Pollution Sources. CoRR Ivan Chuprov, Denis Derkach, Dmitry S. Efremenko, Aleksei Kychkin
2025	—	`conf`	Distilling Normalizing Flows. CVPR Workshops Steven Walton, Valeriy Klyukin, Maksim Artemev, Denis Derkach, Nikita Orlov, Humphrey Shi
2025	J	`jnl`	Distilling Normalizing Flows. CoRR Steven Walton, Valeriy Klyukin, Maksim Artemev, Denis Derkach, Nikita Orlov, Humphrey Shi
2025	J	`jnl`	Learning to Hear Broken Motors: Signature-Guided Data Augmentation for Induction-Motor Diagnostics. CoRR Saraa Ali, Aleksandr Khizhik, Stepan Svirin, Artem Ryzhikov, Denis Derkach
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	A	`conf`	Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space. ECAI Tigran Ramazyan, Mikhail Hushchyn, Denis Derkach
2024	J	`jnl`	Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space. CoRR Tigran Ramazyan, Mikhail Hushchyn, Denis Derkach
2024	J	`jnl`	Intelligent Algorithms For Signature Diagnostics Of Three-Phase Motors. CoRR Stepan Svirin, Artem Ryzhikov, Saraa Ali, Denis Derkach
2023	J	`jnl`	Latent Stochastic Differential Equations for Change Point Detection. IEEE Access Artem Ryzhikov, Mikhail Hushchyn, Denis Derkach
2023	J	`jnl`	Symbolic expression generation PeerJ Comput. Sci. Sergei Popov, Mikhail Lazarev, Vladislav Belavin, Denis Derkach, Andrey Ustyuzhanin
2023	J	`jnl`	Symbolic expression generation via Variational Auto-Encoder. CoRR Sergei Popov, Mikhail Lazarev, Vladislav Belavin, Denis Derkach, Andrey Ustyuzhanin
2023	J	`jnl`	The LHCb ultra-fast simulation option, Lamarr: design and validation. CoRR 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
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`	Latent Neural Stochastic Differential Equations for Change Point Detection. CoRR Artem Ryzhikov, Mikhail Hushchyn, Denis Derkach
2022	J	`jnl`	Supernova Light Curves Approximation based on Neural Network Models. CoRR Mariia Demianenko, Ekaterina Samorodova, Mikhail Sysak, Aleksandr Shiriaev, Konstantin L. Malanchev, Denis Derkach, Mikhail Hushchyn
2022	J	`jnl`	Toward an understanding of the properties of neural network approaches for supernovae light curve approximation. CoRR Mariia Demianenko, Konstantin L. Malanchev, Ekaterina Samorodova, Mikhail Sysak, Aleksandr Shiriaev, Denis Derkach, Mikhail Hushchyn
2022	J	`jnl`	Towards Reliable Neural Generative Modeling of Detectors. CoRR Lucio Anderlini, Matteo Barbetti, Denis Derkach, Nikita Kazeev, Artem Maevskiy, Sergei Mokhnenko
2021	J	`jnl`	NFAD: fixing anomaly detection using normalizing flows. PeerJ Comput. Sci. Artem Ryzhikov, Maxim Borisyak, Andrey Ustyuzhanin, Denis Derkach
2021	J	`jnl`	Photometric data-driven classification of Type Ia supernovae in the open Supernova Catalog. Astron. Comput. Stanislav Dobryakov, Konstantin L. Malanchev, Denis Derkach, Mikhail Hushchyn
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`	Online Neural Networks for Change-Point Detection. CoRR Mikhail Hushchyn, Kenenbek Arzymatov, Denis Derkach
2020	J	`jnl`	Photometric Data-driven Classification of Type Ia Supernovae in the Open Supernova Catalog. CoRR Stanislav Dobryakov, Konstantin L. Malanchev, Denis Derkach, Mikhail Hushchyn
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
2020	J	`jnl`	Variational Dropout Sparsification for Particle Identification speed-up. CoRR Artem Ryzhikov, Denis Derkach, Mikhail Hushchyn
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
2019	J	`jnl`	Fast Data-Driven Simulation of Cherenkov Detectors Using Generative Adversarial Networks. CoRR Artem Maevskiy, Denis Derkach, Nikita Kazeev, Andrey Ustyuzhanin, Maksim Artemev, Lucio Anderlini
2019	J	`jnl`	Normalizing flows for deep anomaly detection. CoRR Artem Ryzhikov, Maxim Borisyak, Andrey Ustyuzhanin, Denis Derkach
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`	LHCb trigger streams optimization. CoRR Denis Derkach, Nikita Kazeev, R. Neychev, A. Panin, I. Trofimov, Andrey Ustyuzhanin, Mika Vesterinen
2017	J	`jnl`	Numerical optimization for Artificial Retina Algorithm. CoRR Maxim Borisyak, Andrey Ustyuzhanin, Denis Derkach, Mikhail Belous
2017	J	`jnl`	Towards automation of data quality system for CERN CMS experiment. CoRR Maxim Borisyak, Fedor Ratnikov, Denis Derkach, Andrey Ustyuzhanin