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ORCIDAlexander Hvatov
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2020 – today
- 2023
[c13]Elizaveta Ivanchik, Alexander Hvatov:
Directed Differential Equation Discovery Using Modified Mutation and Cross-Over Operators. CEC 2023: 1-10- [c12]Mikhail Maslyaev
, Alexander Hvatov:
Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery. GECCO Companion 2023: 603-606 - [i13]Mikhail Maslyaev, Alexander Hvatov:
Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery. CoRR abs/2306.17038 (2023) - [i12]Alexander Hvatov, Roman V. Titov:
Towards true discovery of the differential equations. CoRR abs/2308.04901 (2023) - [i11]Elizaveta Ivanchik, Alexander Hvatov:
Directed differential equation discovery using modified mutation and cross-over operators. CoRR abs/2308.04996 (2023) - [i10]Mikhail Masliaev, Ilya Markov, Alexander Hvatov:
Towards stable real-world equation discovery with assessing differentiating quality influence. CoRR abs/2311.05787 (2023) - 2022
- [j3]Nikolay O. Nikitin, Ilia Revin, Alexander Hvatov, Pavel Vychuzhanin, Anna V. Kalyuzhnaya:
Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea. Comput. Geosci. 161: 105061 (2022) - [c11]Mikhail Maslyaev, Alexander Hvatov:
Solver-Based Fitness Function for the Data-Driven Evolutionary Discovery of Partial Differential Equations. CEC 2022: 1-8 - [c10]Alexander Hvatov:
Data-Driven Approach for the Floquet Propagator Inverse Problem Solution. ICASSP 2022: 3813-3817 - [c9]Damir Aminev, Nikita Demyanchuk, Alexander Hvatov:
On a Structure of an Automated Differential Equation Solver Based on Machine Learning Methods. ISDA (1) 2022: 438-447 - [i9]Alexander Hvatov, Tatiana Tikhonova:
Automated differential equation solver based on the parametric approximation optimization. CoRR abs/2205.05383 (2022) - [i8]Yakov Golovanev, Alexander Hvatov:
On the balance between the training time and interpretability of neural ODE for time series modelling. CoRR abs/2206.03304 (2022) - 2021
- [j2]Anna V. Kalyuzhnaya, Nikolay O. Nikitin, Alexander Hvatov, Mikhail Maslyaev, Mikhail Yachmenkov, Alexander Boukhanovsky:
Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning. Entropy 23(1): 28 (2021) - [j1]Mikhail Maslyaev, Alexander Hvatov, Anna V. Kalyuzhnaya:
Partial differential equations discovery with EPDE framework: Application for real and synthetic data. J. Comput. Sci. 53: 101345 (2021) - [c8]Mikhail Maslyaev, Alexander Hvatov:
Multi-Objective Discovery of PDE Systems Using Evolutionary Approach. CEC 2021: 596-603 - [c7]Nikolay O. Nikitin, Alexander Hvatov, Iana S. Polonskaia, Anna V. Kalyuzhnaya, Georgii V. Grigorev, Xiaohao Wang, Xiang Qian:
Generative design of microfluidic channel geometry using evolutionary approach. GECCO Companion 2021: 59-60 - [c6]Alexander Hvatov, Mikhail Maslyaev, Iana S. Polonskaya, Mikhail Sarafanov, Mark Merezhnikov, Nikolay O. Nikitin:
Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models. OL2A 2021: 72-85 - [i7]Alexander Hvatov:
Partial differential equation solver based on optimization methods. CoRR abs/2103.02294 (2021) - [i6]Nikolay O. Nikitin, Ilia Revin, Alexander Hvatov, Pavel Vychuzhanin, Anna V. Kalyuzhnaya:
Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea. CoRR abs/2103.02598 (2021) - [i5]Mikhail Maslyaev, Alexander Hvatov:
Multi-objective discovery of PDE systems using evolutionary approach. CoRR abs/2103.06739 (2021) - [i4]Alexander Hvatov, Mikhail Maslyaev, Iana S. Polonskaya, Mikhail Sarafanov, Mark Merezhnikov, Nikolay O. Nikitin:
Model-agnostic multi-objective approach for the evolutionary discovery of mathematical models. CoRR abs/2107.03146 (2021) - 2020
- [c5]Anna V. Kalyuzhnaya, Nikolay O. Nikitin, Pavel Vychuzhanin, Alexander Hvatov, Alexander Boukhanovsky:
Automatic evolutionary learning of composite models with knowledge enrichment. GECCO Companion 2020: 43-44 - [c4]Alexander Hvatov, Mikhail Maslyaev:
The data-driven physical-based equations discovery using evolutionary approach. GECCO Companion 2020: 129-130 - [c3]Mikhail Maslyaev, Alexander Hvatov, Anna V. Kalyuzhnaya:
Data-Driven Partial Differential Equations Discovery Approach for the Noised Multi-dimensional Data. ICCS (2) 2020: 86-100 - [i3]Alexander Hvatov, Mikhail Maslyaev:
The data-driven physical-based equations discovery using evolutionary approach. CoRR abs/2004.01680 (2020)
2010 – 2019
- 2019
- [c2]Nikolay O. Nikitin, Pavel Vychuzhanin, Alexander Hvatov, Irina Deeva, Anna V. Kalyuzhnaya, Sergey V. Kovalchuk:
Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study. GECCO (Companion) 2019: 1583-1591 - [c1]Mikhail Maslyaev, Alexander Hvatov, Anna V. Kalyuzhnaya:
Data-Driven Partial Derivative Equations Discovery with Evolutionary Approach. ICCS (5) 2019: 635-641 - [i2]Michail Maslyaev, Alexander Hvatov, Anna V. Kalyuzhnaya:
Data-driven PDE discovery with evolutionary approach. CoRR abs/1903.08011 (2019) - 2018
- [i1]Alexander Hvatov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Sergey S. Kosukhin:
Adaptation of NEMO-LIM3 model for multigrid high resolution Arctic simulation. CoRR abs/1810.03657 (2018)
Coauthor Index
aka: Mikhail Maslyaev
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