Калюжная Анна Владимировна

к.т.н.
Публикаций
46
Цитирований
188
Индекс Хирша
7
Публикаций
45
Цитирований
215
Индекс Хирша
8
Необходимо авторизоваться.
Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea
Nikitin N.O., Revin I., Hvatov A., Vychuzhanin P., Kalyuzhnaya A.V.
Q1 Computers and Geosciences 2022 цитирований: 2
Single Red Blood Cell Hydrodynamic Traps via the Generative Design
Grigorev G.V., Nikitin N.O., Hvatov A., Kalyuzhnaya A.V., Lebedev A.V., Wang X., Qian X., Maksimov G.V., Lin L.
Q2 Micromachines 2022 цитирований: 0
Open Access
Open access
Automated evolutionary approach for the design of composite machine learning pipelines
Nikitin N.O., Vychuzhanin P., Sarafanov M., Polonskaia I.S., Revin I., Barabanova I.V., Maximov G., Kalyuzhnaya A.V., Boukhanovsky A.
Q1 Future Generation Computer Systems 2022 цитирований: 7
A Multimodal Approach to Synthetic Personal Data Generation with Mixed Modelling: Bayesian Networks, GAN’s and Classification Models
Deeva I., Mossyayev A., Kalyuzhnaya A.V.
Q4 Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering 2022 цитирований: 0
Open Access
Open access
A method of generative model design based on irregular data in application to heat transfer problems
Bykov N., Hvatov A., Kalyuzhnaya A., Boukhanovsky A.
Q4 Journal of Physics: Conference Series 2021 цитирований: 0
Open Access
Open access
Generative design of microfluidic channel geometry using evolutionary approach
Nikitin N.O., Hvatov A., Polonskaia I.S., Kalyuzhnaya A.V., Grigorev G.V., Wang X., Qian X.
GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion 2021 цитирований: 1
Partial differential equations discovery with EPDE framework: Application for real and synthetic data [Formula presented]
Maslyaev M., Hvatov A., Kalyuzhnaya A.V.
Q1 Journal of Computational Science 2021 цитирований: 5
MIxBN: Library for learning Bayesian networks from mixed data
Bubnova A.V., Deeva I., Kalyuzhnaya A.V.
Q2 Procedia Computer Science 2021 цитирований: 2
Open Access
Open access
Towards generative design of computationally efficient mathematical models with evolutionary learning
Kalyuzhnaya A.V., Nikitin N.O., Hvatov A., Maslyaev M., Yachmenkov M., Boukhanovsky A.
Q2 Entropy 2021 цитирований: 7
Open Access
Open access
Multi-Objective Evolutionary Design of Composite Data-Driven Models
Polonskaia I.S., Nikitin N.O., Revin I., Vychuzhanin P., Kalyuzhnaya A.V.
2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings 2021 цитирований: 1
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
Deeva I., Bubnova A., Andriushchenko P., Voskresenskiy A., Bukhanov N., Nikitin N.O., Kalyuzhnaya A.V.
Q2 Lecture Notes in Computer Science 2021 цитирований: 0
Open Access
Open access
A machine learning approach for remote sensing data gap-filling with open-source implementation: An example regarding land surface temperature, surface albedo and ndvi
Sarafanov M., Kazakov E., Nikitin N.O., Kalyuzhnaya A.V.
Q1 Remote Sensing 2020 цитирований: 18
Open Access
Open access
Bayesian Networks-based personal data synthesis
Deeva I., Andriushchenko P.D., Kalyuzhnaya A.V., Boukhanovsky A.V.
ACM International Conference Proceeding Series 2020 цитирований: 1
Automatic evolutionary learning of composite models with knowledge enrichment
Kalyuzhnaya A.V., Nikitin N.O., Vychuzhanin P., Hvatov A., Boukhanovsky A.
GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion 2020 цитирований: 6
Discovery of the data-driven models of continuous metocean process in form of nonlinear ordinary differential equations
Maslyaev M., Hvatov A., Kalyuzhnaya A.
Q2 Procedia Computer Science 2020 цитирований: 1
Open Access
Open access
Всего публикаций
44
Всего цитирований
188
Цитирований на публикацию
4.27
Среднее число публикаций в год
4
Среднее число соавторов
3.45
Годы публикаций
2012-2022 (11 лет)
h-index
7
i10-index
3
m-index
0.64
o-index
14
g-index
11
w-index
2
Описание метрик
h-index
Учёный имеет индекс h, если h из его N статей цитируются как минимум h раз каждая, в то время как оставшиеся (N - h) статей цитируются не более чем h раз каждая.
i10-index
Число статей автора, получивших не менее 10 ссылок каждая.
m-index
m-индекс ученого численно равен отношению его h-индекса к количеству лет, прошедших с момента первой публикации.
o-index
Среднее геометрическое h-индекса и числа цитирований наиболее цитируемой статьи ученого.
g-index
Для данного множества статей, отсортированного в порядке убывания количества цитирований, которые получили эти статьи, g-индекс это наибольшее число, такое что g самых цитируемых статей получили (суммарно) не менее g2 цитирований.
w-index
Если w статей ученого имеют не менее 10w цитирований каждая и другие статьи меньше, чем 10(w+1) цитирований, то w-индекс исследователя равен w.
  • Мы не учитываем публикации, у которых нет DOI.
  • Публикации с конференций и главы книг не учитываются в графиках «Журналы» и «Издатели».
  • Статистика пересчитывается раз в сутки.
В этом разделе отображаются профили ученых, зарегистрированных на платформе. Чтобы отображался полный список, приглашайте коллег зарегистрироваться.
Общих публикаций: 21
Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea
Nikitin N.O., Revin I., Hvatov A., Vychuzhanin P., Kalyuzhnaya A.V.
Q1 Computers and Geosciences 2022 цитирований: 2
Single Red Blood Cell Hydrodynamic Traps via the Generative Design
Grigorev G.V., Nikitin N.O., Hvatov A., Kalyuzhnaya A.V., Lebedev A.V., Wang X., Qian X., Maksimov G.V., Lin L.
Q2 Micromachines 2022 цитирований: 0
Open Access
Open access
Automated evolutionary approach for the design of composite machine learning pipelines
Nikitin N.O., Vychuzhanin P., Sarafanov M., Polonskaia I.S., Revin I., Barabanova I.V., Maximov G., Kalyuzhnaya A.V., Boukhanovsky A.
Q1 Future Generation Computer Systems 2022 цитирований: 7
Generative design of microfluidic channel geometry using evolutionary approach
Nikitin N.O., Hvatov A., Polonskaia I.S., Kalyuzhnaya A.V., Grigorev G.V., Wang X., Qian X.
GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion 2021 цитирований: 1
Towards generative design of computationally efficient mathematical models with evolutionary learning
Kalyuzhnaya A.V., Nikitin N.O., Hvatov A., Maslyaev M., Yachmenkov M., Boukhanovsky A.
Q2 Entropy 2021 цитирований: 7
Open Access
Open access
Multi-Objective Evolutionary Design of Composite Data-Driven Models
Polonskaia I.S., Nikitin N.O., Revin I., Vychuzhanin P., Kalyuzhnaya A.V.
2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings 2021 цитирований: 1
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
Deeva I., Bubnova A., Andriushchenko P., Voskresenskiy A., Bukhanov N., Nikitin N.O., Kalyuzhnaya A.V.
Q2 Lecture Notes in Computer Science 2021 цитирований: 0
Open Access
Open access
A machine learning approach for remote sensing data gap-filling with open-source implementation: An example regarding land surface temperature, surface albedo and ndvi
Sarafanov M., Kazakov E., Nikitin N.O., Kalyuzhnaya A.V.
Q1 Remote Sensing 2020 цитирований: 18
Open Access
Open access
Automatic evolutionary learning of composite models with knowledge enrichment
Kalyuzhnaya A.V., Nikitin N.O., Vychuzhanin P., Hvatov A., Boukhanovsky A.
GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion 2020 цитирований: 6
Structural Evolutionary Learning for Composite Classification Models
Nikitin N.O., Polonskaia I.S., Vychuzhanin P., Barabanova I.V., Kalyuzhnaya A.V.
Q2 Procedia Computer Science 2020 цитирований: 9
Open Access
Open access
Adaptation of NEMO-LIM3 model for multigrid high resolution Arctic simulation
Hvatov A., Nikitin N.O., Kalyuzhnaya A.V., Kosukhin S.S.
Q1 Ocean Modelling 2019 цитирований: 5
Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration
Nikitin N.O., Vychuzhanin P., Hvatov A., Deeva I., Kalyuzhnaya A.V., Kovalchuk S.V.
GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion 2019 цитирований: 2
Pattern Recognition in Non-Stationary Environmental Time Series Using Sparse Regression
Deeva I., Nikitin N.O., Kaluyzhnaya A.V.
Q2 Procedia Computer Science 2019 цитирований: 2
Open Access
Open access
Robust Ensemble-Based Evolutionary Calibration of the Numerical Wind Wave Model
Vychuzhanin P., Nikitin N.O., Kalyuzhnaya A.V.
Q2 Lecture Notes in Computer Science 2019 цитирований: 1
Open Access
Open access
Towards management of complex modeling through a hybrid evolutionary identification
Kovalchuk S.V., Metsker O.G., Funkner A.A., Kisliakovskii I.O., Nikitin N.O., Kalyuzhnaya A.V., Vaganov D.A., Bochenina K.O.
GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion 2018 цитирований: 0
Никитин Николай
🤝 🥼
0000-0002-6839-9957
к.т.н.
ИТМО
28 публикаций
111 цитирований
Области научных интересов
Математическое моделирование
Машинное обучение
Общих публикаций: 13
Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea
Nikitin N.O., Revin I., Hvatov A., Vychuzhanin P., Kalyuzhnaya A.V.
Q1 Computers and Geosciences 2022 цитирований: 2
Single Red Blood Cell Hydrodynamic Traps via the Generative Design
Grigorev G.V., Nikitin N.O., Hvatov A., Kalyuzhnaya A.V., Lebedev A.V., Wang X., Qian X., Maksimov G.V., Lin L.
Q2 Micromachines 2022 цитирований: 0
Open Access
Open access
A method of generative model design based on irregular data in application to heat transfer problems
Bykov N., Hvatov A., Kalyuzhnaya A., Boukhanovsky A.
Q4 Journal of Physics: Conference Series 2021 цитирований: 0
Open Access
Open access
Generative design of microfluidic channel geometry using evolutionary approach
Nikitin N.O., Hvatov A., Polonskaia I.S., Kalyuzhnaya A.V., Grigorev G.V., Wang X., Qian X.
GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion 2021 цитирований: 1
Partial differential equations discovery with EPDE framework: Application for real and synthetic data [Formula presented]
Maslyaev M., Hvatov A., Kalyuzhnaya A.V.
Q1 Journal of Computational Science 2021 цитирований: 5
Towards generative design of computationally efficient mathematical models with evolutionary learning
Kalyuzhnaya A.V., Nikitin N.O., Hvatov A., Maslyaev M., Yachmenkov M., Boukhanovsky A.
Q2 Entropy 2021 цитирований: 7
Open Access
Open access
Automatic evolutionary learning of composite models with knowledge enrichment
Kalyuzhnaya A.V., Nikitin N.O., Vychuzhanin P., Hvatov A., Boukhanovsky A.
GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion 2020 цитирований: 6
Discovery of the data-driven models of continuous metocean process in form of nonlinear ordinary differential equations
Maslyaev M., Hvatov A., Kalyuzhnaya A.
Q2 Procedia Computer Science 2020 цитирований: 1
Open Access
Open access
Data-driven partial differential equations discovery approach for the noised multi-dimensional data
Maslyaev M., Hvatov A., Kalyuzhnaya A.
Q2 Lecture Notes in Computer Science 2020 цитирований: 2
Open Access
Open access
Adaptation of NEMO-LIM3 model for multigrid high resolution Arctic simulation
Hvatov A., Nikitin N.O., Kalyuzhnaya A.V., Kosukhin S.S.
Q1 Ocean Modelling 2019 цитирований: 5
Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration
Nikitin N.O., Vychuzhanin P., Hvatov A., Deeva I., Kalyuzhnaya A.V., Kovalchuk S.V.
GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion 2019 цитирований: 2
Data-driven partial derivative equations discovery with evolutionary approach
Maslyaev M., Hvatov A., Kalyuzhnaya A.
Q2 Lecture Notes in Computer Science 2019 цитирований: 5
Open Access
Open access
Anomalies Detection in Metocean Simulation Results Using Convolutional Neural Networks
Vychuzhanin P., Hvatov A., Kalyuzhnaya A.V.
Q2 Procedia Computer Science 2018 цитирований: 1
Open Access
Open access
Хватов Александр
0000-0002-5222-583X
ИТМО
31 публикация
109 цитирований
Общих публикаций: 7
A Multimodal Approach to Synthetic Personal Data Generation with Mixed Modelling: Bayesian Networks, GAN’s and Classification Models
Deeva I., Mossyayev A., Kalyuzhnaya A.V.
Q4 Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering 2022 цитирований: 0
Open Access
Open access
MIxBN: Library for learning Bayesian networks from mixed data
Bubnova A.V., Deeva I., Kalyuzhnaya A.V.
Q2 Procedia Computer Science 2021 цитирований: 2
Open Access
Open access
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
Deeva I., Bubnova A., Andriushchenko P., Voskresenskiy A., Bukhanov N., Nikitin N.O., Kalyuzhnaya A.V.
Q2 Lecture Notes in Computer Science 2021 цитирований: 0
Open Access
Open access
Bayesian Networks-based personal data synthesis
Deeva I., Andriushchenko P.D., Kalyuzhnaya A.V., Boukhanovsky A.V.
ACM International Conference Proceeding Series 2020 цитирований: 1
Analysis of parameters of oil and gas fields using Bayesian networks
Andriushchenko P.D., Deeva I.U., Kalyuzhnaya A.V., Bubnova A.V., Voskresenskiy A.G., Bukhanov N.V.
Data Science in Oil and Gas 2020 2020 цитирований: 1
Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration
Nikitin N.O., Vychuzhanin P., Hvatov A., Deeva I., Kalyuzhnaya A.V., Kovalchuk S.V.
GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion 2019 цитирований: 2
Pattern Recognition in Non-Stationary Environmental Time Series Using Sparse Regression
Deeva I., Nikitin N.O., Kaluyzhnaya A.V.
Q2 Procedia Computer Science 2019 цитирований: 2
Open Access
Open access
Деева Ирина
ИТМО
10 публикаций
18 цитирований
Общих публикаций: 5
Partial differential equations discovery with EPDE framework: Application for real and synthetic data [Formula presented]
Maslyaev M., Hvatov A., Kalyuzhnaya A.V.
Q1 Journal of Computational Science 2021 цитирований: 5
Towards generative design of computationally efficient mathematical models with evolutionary learning
Kalyuzhnaya A.V., Nikitin N.O., Hvatov A., Maslyaev M., Yachmenkov M., Boukhanovsky A.
Q2 Entropy 2021 цитирований: 7
Open Access
Open access
Discovery of the data-driven models of continuous metocean process in form of nonlinear ordinary differential equations
Maslyaev M., Hvatov A., Kalyuzhnaya A.
Q2 Procedia Computer Science 2020 цитирований: 1
Open Access
Open access
Data-driven partial differential equations discovery approach for the noised multi-dimensional data
Maslyaev M., Hvatov A., Kalyuzhnaya A.
Q2 Lecture Notes in Computer Science 2020 цитирований: 2
Open Access
Open access
Data-driven partial derivative equations discovery with evolutionary approach
Maslyaev M., Hvatov A., Kalyuzhnaya A.
Q2 Lecture Notes in Computer Science 2019 цитирований: 5
Open Access
Open access
Масляев Михаил
0000-0001-5595-0802
ИТМО
11 публикаций
28 цитирований
Общих публикаций: 3
MIxBN: Library for learning Bayesian networks from mixed data
Bubnova A.V., Deeva I., Kalyuzhnaya A.V.
Q2 Procedia Computer Science 2021 цитирований: 2
Open Access
Open access
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
Deeva I., Bubnova A., Andriushchenko P., Voskresenskiy A., Bukhanov N., Nikitin N.O., Kalyuzhnaya A.V.
Q2 Lecture Notes in Computer Science 2021 цитирований: 0
Open Access
Open access
Analysis of parameters of oil and gas fields using Bayesian networks
Andriushchenko P.D., Deeva I.U., Kalyuzhnaya A.V., Bubnova A.V., Voskresenskiy A.G., Bukhanov N.V.
Data Science in Oil and Gas 2020 2020 цитирований: 1
Бубнова Анна
ИТМО
3 публикации
3 цитирования
Общих публикаций: 3
Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea
Nikitin N.O., Revin I., Hvatov A., Vychuzhanin P., Kalyuzhnaya A.V.
Q1 Computers and Geosciences 2022 цитирований: 2
Automated evolutionary approach for the design of composite machine learning pipelines
Nikitin N.O., Vychuzhanin P., Sarafanov M., Polonskaia I.S., Revin I., Barabanova I.V., Maximov G., Kalyuzhnaya A.V., Boukhanovsky A.
Q1 Future Generation Computer Systems 2022 цитирований: 7
Multi-Objective Evolutionary Design of Composite Data-Driven Models
Polonskaia I.S., Nikitin N.O., Revin I., Vychuzhanin P., Kalyuzhnaya A.V.
2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings 2021 цитирований: 1
Ревин Илья
0000-0002-4459-8724
ИТМО
4 публикации
12 цитирований
Общих публикаций: 2
Automated evolutionary approach for the design of composite machine learning pipelines
Nikitin N.O., Vychuzhanin P., Sarafanov M., Polonskaia I.S., Revin I., Barabanova I.V., Maximov G., Kalyuzhnaya A.V., Boukhanovsky A.
Q1 Future Generation Computer Systems 2022 цитирований: 7
A machine learning approach for remote sensing data gap-filling with open-source implementation: An example regarding land surface temperature, surface albedo and ndvi
Sarafanov M., Kazakov E., Nikitin N.O., Kalyuzhnaya A.V.
Q1 Remote Sensing 2020 цитирований: 18
Open Access
Open access
Сарафанов Михаил
0000-0002-2459-4486
ИТМО
11 публикаций
29 цитирований