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Избранные публикации пользователей суперкомпьютерного комплекса НИУ ВШЭ

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Q1Q2Q3A*A
20232+2+200000204
202234+23+1661308
20217943185204329
202037
149233020
20196
3201102
Итого1588547132511359

Публикации о суперкомпьютерном комплексе НИУ ВШЭ
  1. Kostenetskiy P.S., Chulkevich R.A., Kozyrev V.I. HPC Resources of the Higher School of Economics // Journal of Physics: Conference Series, 2021. Vol. 1740, No.1. P. 012050. DOI: 10.1088/1742-6596/1740/1/012050 [Текст в формате PDF]
  2. Voevodin V.V., Chulkevich R.A., Kostenetskiy P.S., Kozyrev V.I. et al. Administration, Monitoring and Analysis of Supercomputers in Russia: a Survey of 10 HPC Centers // Supercomputer Frontiers and Innovations, 2021. Vol. 3, No. 3. P. 82 - 103. DOI: 10.14529/jsfi210305 (Q2) [Текст в формате PDF]
  3. Костенецкий П.С., Козырев В.И., Чулкевич Р.А., Шамсутдинов А.Б. Свидетельство о государственной регистрации программы для ЭВМ "HPC TaskMaster - система мониторинга эффективности задач суперкомпьютера". 18 ноября 2021. [Сертификат в формате PDF] 
  4. Kostenetskiy P.S.Chulkevich R.A., Kozyrev V.I., Shamsutdinov A.B. HPC TaskMaster - Task Efficiency Monitoring System for the Supercomputer Center // Communications in Computer and Information Science 2022. DOI: 10.1007/978-3-031-11623-0_2
  5. Костенецкий П.С., Шамсутдинов А.Б., Чулкевич Р.А., Козырев В.И. HPC TaskMaster – система мониторинга эффективности задач суперкомпьютера // Russian Supercomputing Days, 2021 [Текст в формате PDF]  [Презентация в формате PDF]
  6. Козырев В.И., Чулкевич Р.А., Костенецкий П.С. Свидетельство о государственной регистрации программы для ЭВМ "Система мониторинга и статистики вычислительного кластера". 09 сентября 2021. [Сертификат в формате PDF] 
  7. Шамсутдинов А.Б., Костенецкий П.С. Разработка системы мониторинга эффективности задач на суперкомпьютере cHARISMa // Параллельные вычислительные технологии ПаВТ'2021, 30 марта - 1 апреля 2021, г. Волгоград

В соответствии с решением НТС СКК, авторы в своих публикациях должны ссылаться на использование ресурсов СК, для чего нужно в разделе Acknowledgments писать следующие формулировки: «This research was supported in part through computational resources of HPC facilities at HSE University» или «Исследование выполнено с использованием суперкомпьютерного комплекса НИУ ВШЭ».

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[1] Kostenetskiy P.S., Chulkevich R.A., Kozyrev V.I. HPC Resources of the Higher School of Economics // Journal of Physics: Conference Series. 2021. Vol. 1740, No. 1. P. 012050. DOI: https://doi.org/10.1088/1742-6596/1740/1/012050

Публикации 2023 г.
  1. Liu D., Wu Y., Vasenko A., Prezhdo O. Grain Boundary Sliding and Distortion Induce Trap States in CsPbBr3: Ab Initio Investigation with Machine Learning Force Field // Nanoscale, vol. 15, p. 285-293, 2023 (Q1)
  2. Wang K., Liu D., Liu L., Li X., Wu H., Sun Z., Li M., Vasenko A., Ding S., Wang F., Xiao C. Isolated Metalloid Tellurium Atomic Cluster on Nitrogen-Doped Carbon Nanosheet for High-Capacity Rechargeable Lithium-CO2 Battery // Nature Communications, 2023 (In print) (Q1)
Публикации 2022 г.
  1. Mason Liang, Mikhail Shishkin, Anastasia Mikhailova, Vladimir Shchur, Rasmus Nielsen Estimating the timing of multiple admixture events using 3-locus Linkage Disequilibrium // PLoS Genetics. 2022. Vol. 18. No. 7. Article e1010281 (Q1)
  2. Igor Kheifets & Peter Phillips, 2021 "Fully modified least squares cointegrating parameter estimation in multicointegrated systems." // Journal of Econometrics, 2022 (In Press) (Q1)
  3. Rudnev M. Associations Between Higher-Order Values Vary with Age, Education, and Income // European Journal of Personality, 2022 (In Press) (Q1)
  4. Panicheva P. Mararitsa L. Sorokin S. Koltsova O. Rosso O. Predicting subjective well-being in a high-risk sample of Russian mental health app users // EPJ Data Science (under review) (Q1)
  5. Panidi K., Vorobiova A., Feurra M., Klucharev V. Posterior parietal cortex is causally involved in reward value but not reward probability during risky choice // готовится к подаче в журнал Nature Neuroscience (Q1)
  6. E. Tararushkin, V. Pisarev, A. Kalinichev. Atomistic simulations of ettringite and its aqueous interfaces Structure and properties revisited with the modified ClayFF force field // Cement and Concrete Research, 2022 (Q1)
  7. A. Potapova, I. Pile, R. Mondaini, E. Burovski, 1D-to-3D crossover on multileg attractive-U Hubbard ladders, Phys Rev B (in print) (Q1)
  8. Zemlyak V., MacInnes W. The Spatial Leaky Competing Accumulator Model // Frontiers of Computer Science, 2022 (Q1)
  9. Liu D., Perez C. M., Vasenko A., Prezhdo O. Ag–Bi Charge Redistribution Creates Deep Traps in Defective Cs2AgBiBr6: Machine Learning Analysis of Density Functional Theory // The Journal of Physical Chemistry Letters. 2022. Vol. 13. No. 16. P. 3645-3651 (Q1)
  10. Bahovadinov M., Kurlov D., Matveenko S., Altshuler B., Shlyapnikov G. Many-body localization transition in a frustrated XY chain // Phys. Rev. B 106, 075107, 2022 (Q1)
  11. S. I. Matveenko, M. S. Bahovadinov, M. A. Baranov, and G. V. Shlyapnikov. Rotons and their damping in elongated dipolar Bose-Einstein condensates // Phys. Rev. A, 106, 013319, 2022 (Q1)
  12. Vasily V.Pisarev, Andrey G.Kalinichev. Couette flow of pentane in clay nanopores: Molecular dynamics simulation // Journal of Molecular Liquids, Volume 366, 2022 (Q1)
  13. L. R. Bakker, M. S. Bahovadinov, D. V. Kurlov, V. Gritsev, A. K. Fedorov, and Dmitry O. Krimer. Driven-Dissipative Time Crystalline Phases in a Two-Mode Bosonic System with Kerr Nonlinearity // Phys. Rev. Lett., 129, 250401 (Q1)
  14. M. S. Bahovadinov, W. Buijsman, A. K. Fedorov, V. Gritsev, and D. V. Kurlov. Many-body localization of Z3 Fock parafermions // Phys. Rev. B, 106, 224205, 2022 (Q1)
  15. Shchur V, Spirin V, Sirotkin D, Burovski E, De Maio N, Corbett-Detig R. VGsim: Scalable viral genealogy simulator for global pandemic // PLoS Computational Biology. 2022. Vol. 18. No. 8. Article e1010409 (Q1)
  16. Chernyavskiy A., Ilvovsky D. Improving Text Generation via Neural Discourse Planning // WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery (ACM), p. 1543-1544, 2022 (CORE A*)
  17. Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines. Local-Global MCMC kernels: the best of both worlds // NeuRIPS 2022 (CORE A*)
  18. Makarov I.A., Bakhanova M.D., Nikolenko S.I., Gerasimova O.A. Self-supervised recurrent depth estimation with attention mechanisms // PeerJ Computer Science 8:e865, 2022 (Q2)
  19. Makarov I.A., Savchenko A, Korovko A, Sherstyuk L, Severin N, Kiselev D, Mikheev A, Babaev D. 2022. Temporal network embedding framework with causal anonymous walks representations // PeerJ Computer Science 8:e858, 2022 (Q2)
  20. Salikov R.F., Yu. Belyy A., Trainov K.P., Velmiskina J.A., Medvedev M.G., Korshunov V.M., Taydakov I.V., Platonov D.N., Tomilov Y.V. Superphotoacidic properties and pH-switched Stokes shifts in electron-deficient 5-hydroxyisoquinolone derivatives // Journal of Photochemistry and Photobiology A: Chemistry, 2022. P. 113808 (Q2)
  21. Maxim Kodryan, Ekaterina Lobacheva, Maksim Nakhodnov, Dmitry P. Vetrov. Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes // NeurIPS 2022 (CORE A*)
  22. Sergey Smetanin. Pulse of the Nation: Observable Subjective Well-Being in Russia Inferred from Social Network Odnoklassniki // Mathematics, 10(16), 2947, 2022 (Q2)
  23. Ioannis Ntoumanis, Olga Agranovich, Anna N. Shestakova, Evgeny Blagovechtchenski, Maria Koriakina, Dzerassa Kadieva, Grigory Kopytin and Iiro P. Jääskeläinen. Altered Cerebral Processing of Videos in Children with Motor Dysfunction Suggests Broad Embodiment of Perceptual Cognitive Functions // J. Pers. Med., 12(11), 1841, 2022 (Q2)
  24. D. I. Ignatov. On the Number of Maximal Antichains in Boolean Lattices forn up to 7 // Lobachevskii Journal of Mathematics (In print) (Q2)
  25. Murod S. Bahovadinov, Denis V. Kurlov, Boris L. Altshuler & Georgy V. Shlyapnikov. Many-body localization of 1D disordered impenetrable two-component fermions // The European Physical Journal D, volume 76, Article number: 116, 2022 (Q3)
  26. Lucas Vicuña, Anastasia Mikhailova, Tomás Norambuena et al. Genomic insights into the recent population history of Mapuche Native Americans // Submitted to eLife, 2022
  27. Koltsova, O. Y., Mararitsa, L. V., Terpilovskii, M. A., Pashakhin S.V. & Sinyavskaya, Y. E. Faces of friendship: Emotional closeness prediction based on subjective and objective data from SNS (draft paper)
  28. Кондратюк Н.Д., Писарев В.В. Теоретические и вычислительные подходы к предсказанию вязкости жидкостей // УФН, 2022
  29. Тарарушкин Е.В., Писарев В.В., Калиничев А.Г. Атомистическое моделирование структурных и динамических свойств водных растворов NaCl и Na2SO4 в межслоевом пространстве эттрингита // Журнал физической химии, 2022
  30. Troshin S., Chirkova N. Probing Pretrained Models of Source Code. // arXiv, 2022
  31. Sergey Mokhnenko, Lucio Anderlini, Matteo Barbetti, Denis Derkach, Nikita Kazeev, Artem Maevskiy. Towards Reliable Neural Generative Modeling of Detectors // arXiv, 2022
  32. Карпов И. А., Крылова Т. В., Тимошенко С. П. Комплексный лингвистический анализ особенностей электронного комментария в социальных сетях // Русский язык в научном освещении. 2022. Т. 1. № 1. С. 1-18
  33. Karpov I., Kartashev N. Transformers for Online Social Network Language Modelling, in: Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2021, Moscow, Russia, December 16 – 18, 2021, Revised Selected Papers. Vol. 12345w: LNCS. Springer Publishing Company, 2022. P. 1-10
  34. Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian, Artemova et al., Dialogue-22 (в печати)
Публикации 2021 г.
  1. Komissarov A., Shchur V. et al. Genomic epidemiology of the early stages of SARS-CoV-2 outbreak in Russia // Nature Communications, 2021 (Q1)
  2. Smetanin, S., Komarov, M. Deep transfer learning baselines for sentiment analysis in Russian // Information Processing & Management, 2021 (Q1)
  3. Russkov A., Chulkevich R., Shchur L. Algorithm for replica redistribution in an implementation of the population annealing method on a hybrid supercomputer architecture // Computer Physics Communications, 2021 (Q1)
  4. Bakulin I., Kondratyuk N,, Lankin A., Norman G. Properties of aqueous 1,4-dioxane solution via molecular dynamics // Journal of Chemical Physics, 2021 (Q1)
  5. Faizullina K., Pchelintsev I., Burovski E. Critical and geometric properties of magnetic polymers across the globule-coil transition // Physical Review E, 2021 (Q1)
  6. Weigel M., Barash L. Y., Shchur L., Janke W. Understanding population annealing Monte Carlo simulations // Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 2021 (Q1)
  7. Ntoumanis I., Shestakova A., et al. Congenital motor dysfunction enhances the variability of neural responses to naturalistic videos // Annals of Clinical and Translational Neurology, 2021 (Q1)
  8. Koltsov S., Ignatenko V., Terpilowski M., Rosso P. Analysis and tuning of hierarchical topic models based on Renyi entropy approach // PeerJ Computer Science, 2021 (Q1)
  9. Kirova E., Pisarev V. The morphological aspect of crystal nucleation in wall-confined supercooled metallic melt // J. Phys.: Condensed Matter, 2021 (Q1)
  10. Koltsova, O. Y., Mararitsa, L. V., Terpilovskii, M. A., & Sinyavskaya, Y. E. Social signature in an online environment: Stability and cognitive limits // Computers in Human Behavior, 2021 (Q1)
  11. Dogonasheva O. et al. Robust universal approach to identify travelling chimeras and synchronized clusters in spiking networks // Chaos Solitons & Fractals, 2021 (Q1)
  12. Antonov D., Burovski E., Shchur L. Mean-field interactions in evolutionary spatial games // Physical Review Research 3, 2021 (Q1)
  13. Kalikin, N. N., Budkov, Y. A., Kolesnikov, A. L., Ivlev, D. V., Krestyaninov, M. A., & Kiselev, M. G. Computation of drug solvation free energy in supercritical CO2: Alternatives to all-atom computer simulations // Fluid Phase Equilibria, 2021 (Q1)
  14. Kalikin, N. N., Oparin, R. D., Kolesnikov, A. L., Budkov, Y. A., & Kiselev, M. G. A crossover of the solid substances solubility in supercritical fluids: What is it in fact? // Journal of Molecular Liquids, 2021 (Q1)
  15. Gurina, D. L., Budkov, Y. A., & Kiselev, M. G. A molecular insight into poly (methyl methacrylate) impregnation with mefenamic acid in supercritical carbon dioxide: A computational simulation // Journal of Molecular Liquids, 2021 (Q1)
  16. A. Antropov, V. Stegailov. Ultrafast diffusion of overpressurized gas filled nanobubbles in UO2 // Journal of Nuclear Materials, 2021 (Q1)
  17. N. Orekhov, N. Kondratyuk, M. Logunov, A. Timralieva, V. Shilovskikh, E.V. Skorb. Insights into the Early Stages of Melamine Cyanurate Nucleation from Aqueous Solution // Crystal Growth and Design, 2021 (Q1)
  18. A. Maevskiy, F. Ratnikov, Zinchenko A., Riabov V. Simulating the time projection chamber responses at the MPD detector using generative adversarial networks // The European Physical Journal C - Particles and Fields. 2021. Vol. 81. Article 599
  19. Chirkova N., Troshin S. Empirical Study of Transformers for Source Code // ESEC/FSE 2021: Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. Association for Computing Machinery (ACM), 2021 (CORE A*)
  20. Lobacheva E., Kodryan M., Chirkova N., Malinin A., Vetrov D. On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay // NeurIPS, 2021 (CORE A*)
  21. Arefyev N., Kharchev D., Shelmanov A. NB-MLM: Efficient Domain Adaptation of Masked Language Models for Sentiment Analysis // Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021 (CORE A*)
  22. Ivanov D., Pshihachev G., Egorov V., Shpilman A. Self-Imitation Learning from Demonstrations, in: NeurIPS'2021 Deep Reinforcement Learning Workshop, 2021 (CORE A*)
  23. Chirkova N., Troshin S. A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code // Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021 (CORE A)
  24. Saparina I., Osokin A. SPARQLing Database Queries from Intermediate Question Decompositions // Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021 (CORE A)
  25. Chirkova N. On the Embeddings of Variables in Recurrent Neural Networks for Source Code // Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021 (CORE A)
  26. Voevodin V.V., Chulkevich R.A., Kostenetskiy P.S., Kozyrev V.I. et al. Administration, Monitoring and Analysis of Supercomputers in Russia: a Survey of 10 HPC Centers // Supercomputer Frontiers and Innovations, 2021 (Q2)
  27. Ghambaryan A., Gutkin B., Klucharev V., Koechlin E. Additively Combining Utilities and Beliefs: Research Gaps and Algorithmic Developments // Frontiers in Neuroscience, 2021 (Q2)
  28. Belavin V., Trofimova E., Ustyuzhanin A. Segmentation of EM showers for neutrino experiments with deep graph neural networks // Journal of Instrumentation. 2021. No. 12. Article P12035 (Q2)
  29. Ntoumanis I., Kopytin G., Blagoveshchensky E., Shestakova A., Bermúdez-Margaretto B., Agranovich O., Jaaskelainen I. Arthrogryposis Multiplex Congenita Enhances the Variability of Neural Responses to Naturalistic Video Scenes // International Journal of Psychophysiology, 2021. Vol. 168. P. 213 (Q2)
  30. Kondratyuk N., Pisarev V. Predicting shear viscosity of 1,1-diphenylethane at high pressures by molecular dynamics methods // Fluid Phase Equilibria. 2021. Vol. 544-545. Article 113100 (Q2)
  31. Kostenetskiy P.S., Chulkevich R.A., Kozyrev V.I. HPC Resources of the Higher School of Economics // Journal of Physics: Conference Series, 2021 (Q3)
  32. Ziganurova L., Shchur L. Local time evolution in Personal Communication Service model // Journal of Physics: Conference Series, 2021 (Q3)
  33. Klimenkova O., Shchur L. Algorithm for foam generation in plane // Journal of Physics: Conference Series, 2021 (Q3)
  34. Guskova M., Shchur L. Immersed boundary simulation of drop stability // Journal of Physics: Conference Series, 2021 (Q3)
  35. Guskova M., Shchur L. Simulation of the Drops Oscillations in the Channel // Smart Innovation, Systems and Technologies, 2021 (Q3)
  36. Zagvozdina K., Burovski E. Exploring the accuracy of the Lattice Boltzmann method // Journal of Physics: Conference Series, 2021 (Q3)
  37. Moskalenko R., Burovski Е., Shchur L. Spatial chaos in the Nowak-May game in three dimensions // Journal of Physics: Conference Series, 2021 (Q3)
  38. Khomutov E. et al. Deep learning based methods for estimating distribution of coalescence rates from genome wide data // Journal of Physics: Conference Series, 2021 (Q3) 
  39. Khomutov E., Arzymatov K., Shchur V. Deep learning based methods for estimating distribution of coalescence rates from genome-wide data // Journal of Physics: Conference Series, 2021 (Q3)
  40. Boldyrev A. et al. Machine Learning in Calorimeter optimization // Journal of Physics: Conference Series, 2021 (Q3)
  41. Faizullina K., Burovski E. Globule-coil transition in the dynamic HP model // Journal of Physics: Conference Series, 2021 (Q3)
  42. Lobashev A. Surface and Volume Reinforced Random Walk // Journal of Physics: Conference Series, 2021 (Q3)
  43. Sergeev F. et al.  Fast simulation of the LHCb electromagnetic calorimeter response using VAEs and GANs // Journal of Physics: Conference Series, 2021 (Q3)
  44. Zarodnyuk A., Trofimova E., Solovyov A., Gradoboev D. Galaxy Clusters Reconstruction // Journal of Physics: Conference Series, 2021 (Q3)
  45. Chertenkov V., Shchur L. Universality classes and machine learning // Journal of Physics: Conference Series, 2021 (Q3)
  46. Belov A., Kurmanova K. The system of predictive analysis of Bank investments using technologies of supercomputer simulation // Journal of Physics: Conference Series, 2021 (Q3)
  47. Shapoval A., Savostianova D., Shnirman M. Predictability and Scaling in a BTW Sandpile on a Self-Similar Lattice // Journal of Statistical Mechanics (Q3)
  48. Arzymatov K., Guschin M., Sapronov A., Belavin V., Gremyachikh L., Karpov M., Ustyuzhanin A. Online detection of failures generated by storage simulator // Journal of Physics: Conference Series. 2021 (Q3)
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  70. Surkov M., Mosin V.,  Yamshchikov I. Do Data-based Curricula Work? // arXiv, 2021
  71. Guskova M., Shchur L. Spectrum of chain oscillation in Poiseuille flow // arXiv, 2021
  72. Svidchenko O., Shpilman A. Maximum Entropy Model-based Reinforcement Learning // arXiv, 2021
  73. Struminsky K., Gadetsky A., Karpushkin D., Vetrov D. Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces // NeurIPS, 2021
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  76. Guskova M., Shchur L. Smart Modelling for Engineering Systems: Proceedings of the International Conference on Computational Methods in Continuum Mechanics (CMCM 2021): Volume 2 Vol. 215: Smart Modelling for Engineering Systems Proceedings of the International Conference on Computational Methods in Continuum Mechanics (CMCM 2021), Volume 2. Part 21: Simulation of the Drops Oscillations in the Channel. Springer Publishing Company, 2021
  77. Mikhailov V., Serikov O., Artemova E. Morph Call: Probing Morphosyntactic Content of Multilingual Transformers, in: Proceedings of the Third Workshop on Computational Typology and Multilingual NLP. Online: Association for Computational Linguistics, 2021. Ch. 10. P. 97-121
Публикации 2020 г.
  1. Kondratyuk N., Lenev D., Pisarev V. Transport coefficients of model lubricants up to 400 MPa from molecular dynamics // J. Chem. Phys., 2020 (Q1)
  2. Kondratyuk N., Pisarev V., Ewen J. P. Probing the high-pressure viscosity of hydrocarbon mixtures using molecular dynamics simulations // J. Chem. Phys. 2020 (Q1)
  3. Gurina D., Budkov, Y., Kiselev M. Impregnation of Poly (methyl methacrylate) with Carbamazepine in Supercritical Carbon Dioxide: Molecular Dynamics Simulation // The Journal of Physical Chemistry B, 2020 (Q1)
  4. Kalikin N., Kurskaya M., Ivlev D., Krestyaninov M., Oparin R., Kolesnikov A., Budkov Y., Idrissi A., Kiselev M. Carbamazepine solubility in supercritical CO2: a comprehensive study // Journal of Molecular Liquids, 2020 (Q1)
  5. Orekhov N., Ostroumova G., Stegailov V. High temperature pure carbon nanoparticle formation: Validation of AIREBO and ReaxFF reactive molecular dynamics // Carbon. V.170, 2020 (Q1)
  6. Anderlini L. et al. Muon identification for LHCb Run 3 // Journal of Instrumentation, 2020 (Q1)
  7. Fedorov I. D., Orekhov N. D., Stegailov V. V. Nonadiabatic effects and excitonlike states during the insulator-to-metal transition in warm dense hydrogen // Physical Review B, 2020 (Q1)
  8. A. Boldyrev et. al. ML-assisted versatile approach to Calorimeter R&D // Journal of Instrumentation, 2020 (Q1)
  9. Antropov A., Stegailov V. Nanobubbles diffusion in bcc uranium: Theory and atomistic modelling // Journal of Nuclear Materials. 2020. Vol. 533. P. 152110 (Q1)
  10. Shirobokov S., Belavin V., Ustyuzhanin A., Kagan M., Baydin‪. G. Black-Box Optimization with Local Generative Surrogates // Advances in Neural Information Processing Systems 33, 2020 (A*)
  11. Lobacheva Е. et al. On Power Laws in Deep Ensembles // NeurIPS, 2020 (A*)
  12. Molchanov D., Lyzhov A., Molchanova Y., Ashukha A., Vetrov D. Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation // Conference on Uncertainty in Artificial Intelligence 2020 (A*)
  13. Guskova M., Shchur V., Shchur L. Simulation of drop oscillation using the lattice Boltzmann method // Lobachevskii Journal of Mathematics, 2020 (Q2)
  14. Osokin A., Sumin D., Lomakin V. OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features // Proceedings of the European Conference on Computer Vision (ECCV), 2020 (Q2)
  15. Guskova M., Shchur L. Drop oscillation modeling // Proceedings Russian Supercomputer Days 2020 (Q3)
  16. Sukhoroslov O., Voloshinov V. Running Many-Task Applications Across Multiple Resources with Everest Platform // RusSCDays-2020 (Q3)
  17. Artemova E., Batura T., Golenkovskaya A., Ivanin V., Ivanov V., Sarkisyan V., Smurov I., Tutubalina E. So what’s the plan? Mining strategic planning documents. In Digital Transformation and Global Society: Proceedings of the 5th International Conference (DTGS 2020), St. Petersburg, Russia, 2020 (Q3)
  18. Karpov I., Glazkova E.: Detecting Automatically Managed Accounts in Online Social Networks: Graph Embedding Approach //Recent Trends in Analysis of Images, Social Networks and Texts. AIST 2020. Communications in Computer and Information Science
  19. Lobashev A., Tamm M. Contrastive Learning Approach for Phase Diagram Construction of the Random Walk Model with Volume and Surface Reinforcement // Conference on Complex Systems 2020
  20. Choi Y. R., Nikolskiy V., Stegailov V. Matrix-Matrix Multiplication Using Multiple GPUs Connected by Nvlink // Proceedings of IEEE: 2020 Global Smart Industry Conference (GloSIC), 2020
  21. Sokolov A.V., Sokolova L.A. COVID-19 dynamic model: balanced identification of general biological and country specific features // Procedia Computer Science, 2020
  22. Ivanin, V., Artemova, E., Batura, T., Ivanov, V., Sarkisyan, V., Tutubalina, E., Smurov, I. Rurebus-2020 shared task: Russian relation extraction for business. In: Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference “Dialog”, 2020
  23. Sokolov A., Sokolova L. Balanced Identification of the COVID-19 Dynamic Model: General Biological and Country Specific Social Features // Procedia Computer Science, 2020
  24. Ashukha A., Lyzhov A., Molchanov D., Vetrov D. Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning // International Conference on Learning Representations, 2020
  25. Chirkova N. Et al. Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? // arXiv:2005.07292, 2020
  26. Gromov V., Baranov P., Tsybakin A. Prediction after a Horizon of Predictability: Non-Predictable Points and Partial Multi-Step Prediction for Chaotic Time Series, 2020
  27. Громов В., Баранов Ф. Прогнозирование хаотических временных рядов на много шагов вперёд // Вестник современных цифровых технологий, 2020
  28. Smirnov S., Voloshinov V., Sukhoroslov O. Integration on the Everest platform of ParaSCIP solvers running on different clusters to solve a common optimization problem” // Preprint ResearchGate, 2020
  29. Sokolov A., Sokolova L. COVID-19 dynamic model: Balanced identification of general biological and country specific social features // ArXiv, 2020
  30. Rudnev M. Political Participation and Basic Values in Europe: Replication and Extension of Vecchione et al. (2015) // OSF "SocArXiv", 2020
  31. Chirkova N. Neural code completion with anonymized variable names // arXiv 2010.12693, 2020
  32. Chirkova N., Troshin S. Empirical Study of Transformers for Source Code // arXiv:2010.07987, 2020
  33. Nikolay Arefyev and Vasily Zhikov. BOS at SemEval-2020 Task 1: Word Sense Induction via Lexical Substitution for Lexical Semantic Change Detection // Proceedings of the Fourteenth Workshop on Semantic Evaluation, 2020
  34. Shpilman A. et. al. Flatland Competition 2020: MAPF and MARL for EfficientTrain Coordination on a Grid World // Proceedings of Machine Learning Research, 2020 
  35. Klyuchnikov N., Trofimov I., Artemova E., Salnikov M., Fedorov M., Burnaev E. V. NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing / arXiv. Series arXiv:[cs.LG], 2020
  36. Kaledin M., Moulines E., Naumov A., Tadic V., Wai H. Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise, in: Proceedings of Machine Learning Research Vol. 125: Proceedings of Thirty Third Conference on Learning Theory, 2020. P. 2144-22033
  37. Karpychev V., Bolgina T., Malyutina S., Zinchenko V., Ushakov V., Ignatyev G., Dragoy O. No Association Between Structural Properties of Corpus Callosum and Handedness: Evidence from the Constrained Spherical Deconvolution Approach // The Russian Journal of Cognitive Science. 2020. Vol. 7. No. 3. P. 68-77
Публикации 2019 г.
  1. Klimenkova O., Menshutin A., Shchur L. Variable-step-length algorithms for a random walk: Hitting probability and computation performance // Computer Physics Communications. 2019. Vol. 241. P. 28-32 (Q1)
  2. Burovski E., Janke W., Guskova M., Shchur L. Acceptance rate is a thermodynamic function in local Monte Carlo algorithms // Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 2019. Vol. 100. No. 6. P. 063303-1-063303-8 (Q1)
  3. Atanov A., Volokhova A., Ashukha A., Sosnovik I., Vetrov D. Semi-Conditional Normalizing Flows for Semi-Supervised Learning // Workshop on Invertible Neural Nets and Normalizing Flows, International Conference on Machine Learning, 2019 (CORE A*)
  4. Klimenkova O., Menshutin A., Shchur L. Influence of the random walk finite step on the first-passage probability // Journal of Physics: Conference Series. 2018. Vol. 955. No. 012009. P. 1-6 (Q3)
  5. Kondratyuk N., Smirnov G., Agarkov A., Osokin A., Nikolskiy V., Semenov A., Stegailov V. Performance and Scalability of Materials Science and Machine Learning Codes on the State-of-Art Hybrid Supercomputer Architecture // Communications in Computer and Information Science, 2019
  6. Gromov V. Chaotic Time Series Prediction: Run for the Horizon // Proc. of  Int. Conf. on Software Test // Machine Learning and Complex Process Analysis (TMPA-2019)
Зарегистрированные программные продукты
  1. Костенецкий П.С., Козырев В.И., Чулкевич Р.А., Шамсутдинов А.Б. Свидетельство о государственной регистрации программы для ЭВМ "HPC TaskMaster - система мониторинга эффективности задач суперкомпьютера". 18 ноября 2021. [Сертификат в формате PDF] 
  2. Козырев В.И., Чулкевич Р.А., Костенецкий П.С. Свидетельство о государственной регистрации программы для ЭВМ "Система мониторинга и статистики вычислительного кластера". 09 сентября 2021. [Сертификат в формате PDF] 

 

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