Deep learning architectures for nonlinear operator functions and nonlinear inverse problems
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Publication:2113263
DOI10.4171/MSL/28zbMath1485.35420arXiv1912.11090MaRDI QIDQ2113263
Maarten V. de Hoop, Christopher A. Wong, Matti Lassas
Publication date: 11 March 2022
Published in: Mathematical Statistics and Learning (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.11090
Learning and adaptive systems in artificial intelligence (68T05) Inverse problems for PDEs (35R30) Neural nets and related approaches to inference from stochastic processes (62M45)
Related Items (4)
Inverse problems on low-dimensional manifolds ⋮ Convergence Rates for Learning Linear Operators from Noisy Data ⋮ A Data-Assisted Two-Stage Method for the Inverse Random Source Problem ⋮ Data-consistent neural networks for solving nonlinear inverse problems
Uses Software
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