Long-time integration of parametric evolution equations with physics-informed DeepONets
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Publication:2683074
DOI10.1016/j.jcp.2022.111855OpenAlexW3170733857MaRDI QIDQ2683074
Publication date: 3 February 2023
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2106.05384
Artificial intelligence (68Txx) Numerical methods for ordinary differential equations (65Lxx) Numerical analysis (65-XX)
Related Items (5)
Multifidelity deep operator networks for data-driven and physics-informed problems ⋮ Data-driven anisotropic finite viscoelasticity using neural ordinary differential equations ⋮ Bi-fidelity modeling of uncertain and partially unknown systems using DeepONets ⋮ Physics-informed deep learning for three-dimensional transient heat transfer analysis of functionally graded materials ⋮ Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations
Uses Software
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