Machine Learning in Differential Equations
A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".
Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 446
Special Issue Editor
Interests: global optimization; neural networks; genetic algorithms; genetic programming
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The aim of this Special Issue is to present recent advances and new machine-learning methods to model and solve differential equations. Topics include but are not limited to:
- Genetic programming and differential equations;
- Grammatical evolution and differential equations;
- Inference of differential equation models;
- Estimation of chaotic ordinary differential equations;
- Time-series forecasting using differential equations;
- Inverse problems and machine learning models;
- Parallel and distributed techniques to solve differential equations;
- Numerical integration in neural ordinary differential equations;
- Recurrent neural networks applied to differential equations;
- Machine learning for continuous-time finance;
- Artificial neural networks for solving fuzzy differential equations;
- Stochastic differential equations and machine learning methods;
- Machine learning of space-fractional differential equations;
- Software specialized to solve differential equations;
- Using differential evolution based methods to solve differential equations;
- Automatic differentiation and differential equations;
- Interval algorithms and differential equations.
Dr. Ioannis G. Tsoulos
Guest Editor
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