research
∙
08/09/2023
Directed differential equation discovery using modified mutation and cross-over operators
The discovery of equations with knowledge of the process origin is a tem...
share
research
∙
08/09/2023
Towards true discovery of the differential equations
Differential equation discovery, a machine learning subfield, is used to...
research
∙
06/29/2023
Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery
Evolutionary differential equation discovery proved to be a tool to obta...
research
∙
06/07/2022
On the balance between the training time and interpretability of neural ODE for time series modelling
Most machine learning methods are used as a black box for modelling. We ...
research
∙
05/11/2022
Automated differential equation solver based on the parametric approximation optimization
The numerical methods for differential equation solution allow obtaining...
research
∙
07/07/2021
Model-agnostic multi-objective approach for the evolutionary discovery of mathematical models
In modern data science, it is often not enough to obtain only a data-dri...
research
∙
03/11/2021
Multi-objective discovery of PDE systems using evolutionary approach
Usually, the systems of partial differential equations (PDEs) are discov...
research
∙
03/03/2021
Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea
The paper describes the usage of intelligent approaches for field develo...
research
∙
03/03/2021
Partial differential equation solver based on optimization methods
The numerical solution methods for partial differential equation (PDE) s...
research
∙
04/03/2020
The data-driven physical-based equations discovery using evolutionary approach
The modern machine learning methods allow one to obtain the data-driven ...
research
∙
03/19/2019
Data-driven PDE discovery with evolutionary approach
The data-driven models allow one to dene the model struc-ture in cases w...
research
∙
10/08/2018
