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Joint Spatiotemporal Spectral Neural Operators for Learning PDEs on Irregular Domains
Abdolmehdi Behroozi, Chaopeng Shen
Learning solution operators for partial differential equations (PDEs) on irregular and geometry-dependent domains remains a central challenge in scientific machine learning. While…
Sensitivity-Constrained Neural Operators for Data-Efficient Forward and Inverse Modeling of Partial Differential Equation Systems
Abdolmehdi Behroozi, Chaopeng Shen, Daniel Kifer +1
Neural operators provide fast surrogates for partial differential equation (PDE) solvers, but their reliability can degrade for high-dimensional spatial inputs and inverse or repea…
Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations
Abdolmehdi Behroozi, Chaopeng Shen and, Daniel Kifer
Parametric differential equations of the form du/dt = f(u, x, t, p) are fundamental in science and engineering. While deep learning frameworks such as the Fourier Neural Operator (…