Development of data‐driven exponential integrators with application to modeling of delay photocurrents
DOI10.1002/NUM.22857OpenAlexW4200474571WikidataQ114235161 ScholiaQ114235161MaRDI QIDQ6090388
Biliana S. Paskaleva, Pavel B. Bochev
Publication date: 16 December 2023
Published in: Numerical Methods for Partial Differential Equations (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/num.22857
Artificial neural networks and deep learning (68T07) Learning and adaptive systems in artificial intelligence (68T05) PDEs in connection with optics and electromagnetic theory (35Q60) System identification (93B30) Statistical mechanics of semiconductors (82D37) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60) Multistep, Runge-Kutta and extrapolation methods for ordinary differential equations (65L06) Electromagnetic theory (general) (78A25) Method of lines for initial value and initial-boundary value problems involving PDEs (65M20) Motion of charged particles (78A35) Waves and radiation in optics and electromagnetic theory (78A40) Methods of ordinary differential equations applied to PDEs (35A24) Numerical methods for stiff equations (65L04) Model reduction in optics and electromagnetic theory (78M34) PDEs on time scales (35R07)
Cites Work
- Unnamed Item
- Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations. Application to transport and continuum mechanics.
- Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- On dynamic mode decomposition: theory and applications
- Exponential integrators
- Dynamic mode decomposition of numerical and experimental data
- MODEL STRUCTURAL INFERENCE USING LOCAL DYNAMIC OPERATORS
- Learning data-driven discretizations for partial differential equations
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