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cs.LG2024
A Multi-Fidelity Graph U-Net Model for Accelerated Physics Simulations
Rini Jasmine Gladstone, Hadi Meidani
Physics-based deep learning frameworks have shown to be effective in accurately modeling the dynamics of complex physical systems with generalization capability across problem inpu…
cs.LG2024
Physics-Informed Geometry-Aware Neural Operator
Weiheng Zhong, Hadi Meidani
Engineering design problems often involve solving parametric Partial Differential Equations (PDEs) under variable PDE parameters and domain geometry. Recently, neural operators hav…
math.NA2024
Physics-informed Discretization-independent Deep Compositional Operator Network
Weiheng Zhong, Hadi Meidani
Solving parametric Partial Differential Equations (PDEs) for a broad range of parameters is a critical challenge in scientific computing. To this end, neural operators, which \text…