Solving inverse-PDE problems with physics-aware neural networks
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Publication:2129334
DOI10.1016/j.jcp.2021.110414OpenAlexW3000220657WikidataQ114163454 ScholiaQ114163454MaRDI QIDQ2129334
Miguel A. Aragon-Calvo, Samira Pakravan, Frédéric Gibou, Pouria A. Mistani
Publication date: 22 April 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2001.03608
Artificial intelligence (68Txx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Partial differential equations of mathematical physics and other areas of application (35Qxx)
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Imaging conductivity from current density magnitude using neural networks* ⋮ JAX-DIPS: neural bootstrapping of finite discretization methods and application to elliptic problems with discontinuities ⋮ TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems ⋮ Applying artificial neural networks to solve the inverse problem of evaluating concentrations in multianalyte mixtures from biosensor signals ⋮ Error-correcting neural networks for semi-Lagrangian advection in the level-set method
Uses Software
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