Biblio
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] Filters: Keyword is Fourier neural operators and Author is Mathias Louboutin [Clear All Filters]
, “Learned multiphysics inversion with differentiable programming and machine learning”, The Leading Edge, vol. 42, pp. 452-516, 2023.
, “Model-Parallel Fourier Neural Operators as Learned Surrogates for Large-Scale Parametric PDEs”, Computers & Geosciences, vol. 178, p. 105402, 2023.
, “The Next Step: Interoperable Domain-Specific Programming”, in SIAM Conference on Computational Science and Engineering, 2023.
, “Solving multiphysics-based inverse problems with learned surrogates and constraints”, Advanced Modeling and Simulation in Engineering Sciences, vol. 10, 2023.
, “Solving PDE-based inverse problems with learned surrogates and constraints”, HotCSE Seminar. 2023.
, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.
, “Amortized velocity continuation with Fourier neural operators”, ML4SEISMIC Partners Meeting. 2022.
, “Effective scaling of numerical surrogates via domain-decomposed Fourier neural operators”, ML4SEISMIC Partners Meeting. 2022.
, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Uncertainty-aware time-lapse CO$_2$ monitoring with learned end-to-end inversion”, ML4SEISMIC Partners Meeting. 2022.
, “Velocity continuation with Fourier neural operators for accelerated uncertainty quantification”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.