SimPINNs: Simulation-Driven Physics-Informed Neural Networks for Enhanced Performance in Nonlinear Inverse Problems

27 September 2023

Papers citing "SimPINNs: Simulation-Driven Physics-Informed Neural Networks for Enhanced Performance in Nonlinear Inverse Problems"

7 / 7 papers shown

Title
Equivariant Imaging: Learning Beyond the Range Space Dongdong Chen Julián Tachella Mike E. Davies SSL 74 102 0 26 Mar 2021
Deep S $^3$ PR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models Christopher A. Metzler Gordon Wetzstein 38 11 0 14 Feb 2020
prDeep: Robust Phase Retrieval with a Flexible Deep Network Christopher A. Metzler Philip Schniter Ashok Veeraraghavan Richard G. Baraniuk OOD 69 169 0 01 Mar 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 108 752 0 20 Jan 2018
Deep Image Prior Dmitry Ulyanov Andrea Vedaldi Victor Lempitsky SupR 114 3,147 0 29 Nov 2017
Phase recovery and holographic image reconstruction using deep learning in neural networks Y. Rivenson Yibo Zhang H. Gunaydin Da Teng Aydogan Ozcan 43 820 0 10 May 2017
Compressed Sensing using Generative Models Ashish Bora A. Jalal Eric Price A. Dimakis 124 808 0 09 Mar 2017