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Solving ill-posed inverse problems using iterative deep neural networks

13 April 2017

Papers citing "Solving ill-posed inverse problems using iterative deep neural networks"

50 / 212 papers shown

Title
Choose a Transformer: Fourier or Galerkin Shuhao Cao 88 256 0 31 May 2021
TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems Hai V. Nguyen T. Bui-Thanh PINN AI4CE 35 9 0 25 May 2021
A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction Liyue Shen Wei Zhao D. Capaldi John M. Pauly Lei Xing 65 29 0 25 May 2021
Feasibility-based Fixed Point Networks Howard Heaton Samy Wu Fung A. Gibali W. Yin 57 26 0 29 Apr 2021
Adversarially learned iterative reconstruction for imaging inverse problems Subhadip Mukherjee Ozan Oktem Carola-Bibiane Schönlieb SSL 81 7 0 30 Mar 2021
Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems William Herzberg D. Rowe A. Hauptmann S. Hamilton GNN MedIm AI4CE 38 35 0 28 Mar 2021
DRO: Deep Recurrent Optimizer for Video to Depth Xiaodong Gu Weihao Yuan Zuozhuo Dai Siyu Zhu Chengzhou Tang Zilong Dong Ping Tan VGen 19 16 0 24 Mar 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 256 236 0 23 Mar 2021
Equivariant neural networks for inverse problems E. Celledoni Matthias Joachim Ehrhardt Christian Etmann B. Owren Carola-Bibiane Schönlieb Ferdia Sherry MedIm AI4CE 83 27 0 23 Feb 2021
Edge Sparse Basis Network: A Deep Learning Framework for EEG Source Localization Chen Wei Kexin Lou Zhengyang Wang Mingqi Zhao D. Mantini Quanying Liu 81 21 0 18 Feb 2021
UVTomo-GAN: An adversarial learning based approach for unknown view X-ray tomographic reconstruction Mona Zehni Zhizhen Zhao GAN 15 4 0 09 Feb 2021
SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees Jiaming Liu Yu Sun Weijie Gan Xiaojian Xu B. Wohlberg Ulugbek S. Kamilov FedML MedIm 89 31 0 22 Jan 2021
DAEs for Linear Inverse Problems: Improved Recovery with Provable Guarantees J. Dhaliwal Kyle Hambrook 113 0 0 13 Jan 2021
Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh-Nagumo ODE J. Rudi J. Bessac Amanda Lenzi 319 33 0 12 Dec 2020
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network Haoyu Wei Florian Schiffers Tobias Würfl Daming Shen Daniel Kim Aggelos K. Katsaggelos O. Cossairt 65 19 0 08 Dec 2020
A feedforward neural network for modelling of average pressure frequency response K. Pettersson Andrey Karzhou Irina Pettersson 31 1 0 03 Dec 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 67 107 0 09 Nov 2020
Solving Inverse Problems with Hybrid Deep Image Priors: the challenge of preventing overfitting Zhaodong Sun Thomas Sanchez Fabian Latorre Volkan Cevher SupR 74 28 0 03 Nov 2020
A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound A. Stanziola Simon Arridge B. Cox B. Treeby 56 34 0 29 Oct 2020
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images Chen-Hsuan Lin Chaoyang Wang Simon Lucey 147 101 0 20 Oct 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 532 2,460 0 18 Oct 2020
Generalized Intersection Algorithms with Fixpoints for Image Decomposition Learning Robin Richter D. H. Thai S. Huckemann 8 2 0 16 Oct 2020
A computationally efficient reconstruction algorithm for circular cone-beam computed tomography using shallow neural networks M. J. Lagerwerf D. Pelt W. J. Palenstijn K. Batenburg 23 14 0 01 Oct 2020
Deep Learning in Photoacoustic Tomography: Current approaches and future directions A. Hauptmann B. Cox 126 131 0 16 Sep 2020
Optimization with learning-informed differential equation constraints and its applications Guozhi Dong M. Hintermueller Kostas Papafitsoros PINN 51 14 0 25 Aug 2020
Human Body Model Fitting by Learned Gradient Descent Mingli Song Xu Chen Otmar Hilliges 3DH 66 101 0 19 Aug 2020
Performance characterization of a novel deep learning-based MR image reconstruction pipeline PhD R. Marc Lebel MedIm 37 85 0 14 Aug 2020
Learned convex regularizers for inverse problems Subhadip Mukherjee Sören Dittmer Zakhar Shumaylov Sebastian Lunz Ozan Oktem Carola-Bibiane Schönlieb 83 80 0 06 Aug 2020
Wasserstein-based Projections with Applications to Inverse Problems Howard Heaton Samy Wu Fung A. Lin Stanley Osher W. Yin 46 3 0 05 Aug 2020
Solving inverse problems using conditional invertible neural networks G. A. Padmanabha N. Zabaras AI4CE 59 64 0 31 Jul 2020
On the unreasonable effectiveness of CNNs A. Hauptmann J. Adler 55 9 0 29 Jul 2020
Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example Nanzhe Wang Haibin Chang Dongxiao Zhang AI4CE 67 61 0 28 Jul 2020
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows Ali Siahkoohi G. Rizzuti Philipp A. Witte Felix J. Herrmann AI4CE 62 16 0 15 Jul 2020
Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset Sören Dittmer T. Kluth Mads Thorstein Roar Henriksen Peter Maass 43 19 0 03 Jul 2020
Ground Truth Free Denoising by Optimal Transport Sören Dittmer Carola-Bibiane Schönlieb Peter Maass OT DiffM 44 2 0 03 Jul 2020
Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations Dongdong Chen Mike E. Davies Mohammad Golbabaee 64 16 0 27 Jun 2020
Multipole Graph Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 230 395 0 16 Jun 2020
Regularization of Inverse Problems by Neural Networks Markus Haltmeier Linh V. Nguyen 72 18 0 06 Jun 2020
Joint learning of variational representations and solvers for inverse problems with partially-observed data Ronan Fablet Lucas Drumetz F. Rousseau 51 18 0 05 Jun 2020
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 58 29 0 02 Jun 2020
MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction Haimiao Zhang Baodong Liu Hengyong Yu Bin Dong 68 62 0 30 May 2020
On Learned Operator Correction in Inverse Problems Sebastian Lunz A. Hauptmann T. Tarvainen Carola-Bibiane Schönlieb Simon Arridge 79 4 0 14 May 2020
Model Reduction and Neural Networks for Parametric PDEs K. Bhattacharya Bamdad Hosseini Nikola B. Kovachki Andrew M. Stuart 242 333 0 07 May 2020
Sparse aNETT for Solving Inverse Problems with Deep Learning D. Obmann Linh V. Nguyen Johannes Schwab Markus Haltmeier 24 7 0 20 Apr 2020
Finding Your (3D) Center: 3D Object Detection Using a Learned Loss David J. Griffiths Jan Boehm Tobias Ritschel 3DPC 103 8 0 06 Apr 2020
GAN-based Priors for Quantifying Uncertainty Dhruv V. Patel Assad A. Oberai BDL UQCV 53 7 0 27 Mar 2020
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow Zachary Teed Jia Deng MDE 277 2,651 0 26 Mar 2020
Applications of Deep Learning for Ill-Posed Inverse Problems Within Optical Tomography A. Peace MedIm 17 0 0 21 Mar 2020
Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods Daniel Otero Baguer Johannes Leuschner Maximilian Schmidt 112 189 0 10 Mar 2020
Neural Operator: Graph Kernel Network for Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar 211 749 0 07 Mar 2020