Multifidelity deep operator networks for data-driven and physics-informed problems

2023/09/01 by Amanda A. Howard, Mauro Perego, George Em Karniadakis +1 · 11 citations
Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Fluid Dynamics and Vibration Analysis #Nuclear Engineering Thermal-Hydraulics

paper · doi:10.1016/j.jcp.2023.112462

Citations

• Exponential Time Differencing for Stiff Systems
• A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems
• Transfer learning based multi-fidelity physics informed deep neural network

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