Deep learning architectures for nonlinear operator functions and
nonlinear inverse problems

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Deep learning architectures for nonlinear operator functions and nonlinear inverse problems

23 December 2019

Maarten V. de Hoop

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Papers citing "Deep learning architectures for nonlinear operator functions and nonlinear inverse problems"

13 / 13 papers shown

Title
Neural Operators Can Play Dynamic Stackelberg Games Guillermo Alvarez Ibrahim Ekren Anastasis Kratsios Xuwei Yang 76 0 0 14 Nov 2024
The learned range test method for the inverse inclusion problem Shiwei Sun Giovanni S. Alberti 66 0 0 01 Nov 2024
DiffusionPDE: Generative PDE-Solving Under Partial Observation Jiahe Huang Guandao Yang Zichen Wang Jeong Joon Park DiffM 97 31 0 25 Jun 2024
Mixture of Experts Soften the Curse of Dimensionality in Operator Learning Anastasis Kratsios Takashi Furuya Jose Antonio Lara Benitez Matti Lassas Maarten V. de Hoop 97 14 0 13 Apr 2024
Learned reconstruction methods for inverse problems: sample error estimates Luca Ratti 67 0 0 21 Dec 2023
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation Jose Antonio Lara Benitez Takashi Furuya F. Faucher Anastasis Kratsios X. Tricoche Maarten V. de Hoop 136 19 0 27 Jan 2023
Neural Inverse Operators for Solving PDE Inverse Problems Roberto Molinaro Yunan Yang Bjorn Engquist Siddhartha Mishra AI4CE 91 41 0 26 Jan 2023
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis Luca Galimberti Anastasis Kratsios Giulia Livieri OOD 125 14 0 24 Oct 2022
Transformer Meets Boundary Value Inverse Problems Ruchi Guo Shuhao Cao Long Chen MedIm 138 23 0 29 Sep 2022
Convergence Rates for Learning Linear Operators from Noisy Data Maarten V. de Hoop Nikola B. Kovachki Nicholas H. Nelsen Andrew M. Stuart 186 58 0 27 Aug 2021
Learning the optimal Tikhonov regularizer for inverse problems Giovanni S. Alberti Ernesto De Vito Matti Lassas Luca Ratti Matteo Santacesaria 81 30 0 11 Jun 2021
Deep neural networks for inverse problems with pseudodifferential operators: an application to limited-angle tomography T. Bubba Mathilde Galinier Matti Lassas M. Prato Luca Ratti S. Siltanen 65 29 0 02 Jun 2020
Solving Traveltime Tomography with Deep Learning Yuwei Fan Lexing Ying 97 15 0 25 Nov 2019