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Spectral operator learning for parametric PDEs without data reliance
In this paper, we introduce the Spectral Coefficient Learning via Operator Network (SCLON), a novel operator learning-based approach for solving parametric partial differential equations (PDEs) without the need for data harnessing.
Unsupervised Legendre-Galerkin Neural Network for Singularly Perturbed Partial Differential Equations
Machine learning methods have been lately used to solve partial differential equations (PDEs) and dynamical systems.
Formation of Singularities in Plasma Ion Dynamics
We study the formation of singularity for the Euler-Poisson system equipped with the Boltzmann relation, which describes the dynamics of ions in an electrostatic plasma.
Analysis of PDEs
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