Automated data-driven approach for gap filling in the time series using evolutionary learning
In the paper, we propose an adaptive data-driven model-based approach for filling the gaps
in time series. The approach is based on the automated evolutionary identification of the …
in time series. The approach is based on the automated evolutionary identification of the …
Data-driven approach for the Floquet propagator inverse problem solution
A Hvatov - ICASSP 2022-2022 IEEE International Conference …, 2022 - ieeexplore.ieee.org
Floquet theory is a classical tool for the analysis of periodic structures' acoustics. However, it
may be challenging to analyze material properties for complex cases, whereas the …
may be challenging to analyze material properties for complex cases, whereas the …
On the balance between the training time and interpretability of neural ODE for time series modelling
Y Golovanev, A Hvatov - arXiv preprint arXiv:2206.03304, 2022 - arxiv.org
Most machine learning methods are used as a black box for modelling. We may try to extract
some knowledge from physics-based training methods, such as neural ODE (ordinary …
some knowledge from physics-based training methods, such as neural ODE (ordinary …
Discovery of multivariable algebraic expressions using evolutionary optimization
J Schvartsberg, A Hvatov - Procedia Computer Science, 2022 - Elsevier
Abstract Machine learning interpretation has a well-established discussion in various areas.
Whereas most interpretation is made after the modelling, one may try to obtain the …
Whereas most interpretation is made after the modelling, one may try to obtain the …
Model-agnostic multi-objective approach for the evolutionary discovery of mathematical models
A Hvatov, M Maslyaev, IS Polonskaya… - … Learning Algorithms and …, 2021 - Springer
In modern data science, it is often not enough to obtain only a data-driven model with a good
prediction quality. On the contrary, it is more interesting to understand the properties of the …
prediction quality. On the contrary, it is more interesting to understand the properties of the …
Multi-objective closed-form algebraic expressions discovery approach application to the synthetic time-series generation
M Merezhnikov, A Hvatov - Procedia Computer Science, 2021 - Elsevier
Time-series modeling is a well-studied topic of classical analysis and machine learning.
However, large datasets are required to obtain the model with a better prediction quality with …
However, large datasets are required to obtain the model with a better prediction quality with …