A neural operator view on U-Nets for inverse imaging problems | Paper Citation Record

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A neural operator view on U-Nets for inverse imaging problems Unresolved cited work

Reference 1

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This paper cites Gradient Step Denoiser for convergent Plug-and-Play.

A neural operator view on U-Nets for inverse imaging problems Gradient Step Denoiser for convergent Plug-and-Play

Reference 2

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This paper cites Plug-and- Play priors for model based reconstruction.

A neural operator view on U-Nets for inverse imaging problems Plug-and- Play priors for model based reconstruction

Reference 3

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Observation d11b541e-a283-4f52-9a3e-8329e6a3361f · outbound

This paper cites Score-based diffusion models as principled priors for inverse imaging.

A neural operator view on U-Nets for inverse imaging problems Score-based diffusion models as principled priors for inverse imaging

Reference 4

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This paper cites Multilevel Diffusion: Infinite Dimensional Score- Based Diffusion Models for Image Generation.

A neural operator view on U-Nets for inverse imaging problems Multilevel Diffusion: Infinite Dimensional Score- Based Diffusion Models for Image Generation

Reference 5

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This paper cites Score-Based Diffusion Models in Function Space.

A neural operator view on U-Nets for inverse imaging problems Score-Based Diffusion Models in Function Space

Reference 6

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This paper cites Generative modeling by estimating gradients of the data distribution.

A neural operator view on U-Nets for inverse imaging problems Generative modeling by estimating gradients of the data distribution

Reference 7

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This paper cites Welker et al.Position-Blind Ptychography: Viability of image recon- struction via data-driven variational inference (in preparation).

A neural operator view on U-Nets for inverse imaging problems Welker et al.Position-Blind Ptychography: Viability of image recon- struction via data-driven variational inference (in preparation)

Reference 8

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This paper cites Provably Robust Score-Based Diffusion Poste- rior Sampling for Plug-and-Play Image Reconstruction.

A neural operator view on U-Nets for inverse imaging problems Provably Robust Score-Based Diffusion Poste- rior Sampling for Plug-and-Play Image Reconstruction

Reference 9

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This paper cites Flow Matching: Markov kernels, stochastic processes and transport plans.

A neural operator view on U-Nets for inverse imaging problems Flow Matching: Markov kernels, stochastic processes and transport plans

Reference 10

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Observation 95cc8c2e-9956-4566-a4a6-d7d41188bf22 · outbound

This paper cites U-Net: Convolutional Net- works for Biomedical Image Segmentation.

A neural operator view on U-Nets for inverse imaging problems U-Net: Convolutional Net- works for Biomedical Image Segmentation

Reference 11

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This paper cites Fully Convolutional Networks for Semantic Segmentation.

A neural operator view on U-Nets for inverse imaging problems Fully Convolutional Networks for Semantic Segmentation

Reference 12

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This paper cites End-to-end Res-Unet based reconstruction algorithm for photoacoustic imaging.

A neural operator view on U-Nets for inverse imaging problems End-to-end Res-Unet based reconstruction algorithm for photoacoustic imaging

Reference 13

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Observation d3a33db7-53fa-4c68-a523-d6507e25500c · outbound

This paper cites Plug-and-Play Image Restoration With Deep Denoiser Prior.

A neural operator view on U-Nets for inverse imaging problems Plug-and-Play Image Restoration With Deep Denoiser Prior

Reference 14

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Observation 8206c3fe-41b6-482a-afaf-b02b34fcbbc8 · outbound

This paper cites Robustness and exploration of variational and machine learning approaches to inverse problems: An overview.

A neural operator view on U-Nets for inverse imaging problems Robustness and exploration of variational and machine learning approaches to inverse problems: An overview

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.778784Z

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Observation b9f19e1d-a630-4492-a403-9ae92b74562d · outbound

This paper cites Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning.

A neural operator view on U-Nets for inverse imaging problems Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning

Reference 16

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Observation f57f9d40-537f-45a3-ac55-a9f053ae85d5 · outbound

This paper cites Neural operator: Learning maps between function spaces with applications to pdes.

A neural operator view on U-Nets for inverse imaging problems Neural operator: Learning maps between function spaces with applications to pdes

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.764913Z

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Observation 16aa7b8b-7e8a-4019-8d67-8be5b3104386 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

A neural operator view on U-Nets for inverse imaging problems Fourier Neural Operator for Parametric Partial Differential Equations

Reference 18

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Observation 465ddc80-ad42-4d7f-b1e8-146d521d1c1c · outbound

This paper cites Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone.

A neural operator view on U-Nets for inverse imaging problems Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.736673Z

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Observation eaf16b77-f5a7-4c67-a32a-d73aff5c8f1a · outbound

This paper cites Fourier neural operator with learned deformations for pdes on general geometries.

A neural operator view on U-Nets for inverse imaging problems Fourier neural operator with learned deformations for pdes on general geometries

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.722885Z

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Observation f900d060-d29c-4c0d-b8d2-d2c973d025b7 · outbound

This paper cites U-shaped factorized Fourier neural operator for solving partial differential equations.

A neural operator view on U-Nets for inverse imaging problems U-shaped factorized Fourier neural operator for solving partial differential equations

Reference 21

Resolution: verified exact; doi, observed 2026-08-07T22:38:15.046056Z

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Observation 97be5fb1-edb4-4608-bc80-bafd3a40ee0b · outbound

This paper cites U-NO: U-shaped Neural Operators.

A neural operator view on U-Nets for inverse imaging problems U-NO: U-shaped Neural Operators

Reference 22

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This paper cites Factorized Fourier Neural Operators.

A neural operator view on U-Nets for inverse imaging problems Factorized Fourier Neural Operators

Reference 23

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Observation 04b2dc67-f398-4dc7-9c01-3498f5773131 · outbound

This paper cites U-FNO—An enhanced Fourier neural operator-based deep-learning model for multiphase flow.

A neural operator view on U-Nets for inverse imaging problems U-FNO—An enhanced Fourier neural operator-based deep-learning model for multiphase flow

Reference 24

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Observation f7e1dfda-7387-4f59-bca6-ed33aaeec9a1 · outbound

This paper cites Neural operators with localized integral and differential kernels.

A neural operator view on U-Nets for inverse imaging problems Neural operators with localized integral and differential kernels

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.666949Z

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This paper cites Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions.

A neural operator view on U-Nets for inverse imaging problems Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.652711Z

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Observation 8a80691a-f6ed-4906-8ee6-fd7c3af01af9 · outbound

This paper cites Aubert and P.

A neural operator view on U-Nets for inverse imaging problems Aubert and P

Reference 27

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This paper cites Sch¨ onlieb.Partial differential equation methods for image in- painting.

A neural operator view on U-Nets for inverse imaging problems Sch¨ onlieb.Partial differential equation methods for image in- painting

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.638444Z

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This paper cites Deep neural networks motivated by par- tial differential equations.

A neural operator view on U-Nets for inverse imaging problems Deep neural networks motivated by par- tial differential equations

Reference 29

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Observation 6420be6e-907c-4c58-947f-aaca5b06ced1 · outbound

This paper cites Representation equivalent neural operators: a framework for alias-free operator learning.

A neural operator view on U-Nets for inverse imaging problems Representation equivalent neural operators: a framework for alias-free operator learning

Reference 30

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Observation cfb24a90-5515-4dd1-8bda-a42957e239d8 · outbound

This paper cites Convolutional neural operators for robust and ac- curate learning of PDEs.

A neural operator view on U-Nets for inverse imaging problems Convolutional neural operators for robust and ac- curate learning of PDEs

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.596122Z

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Observation e4447d4d-5b8c-4abc-8777-7e7f09344d75 · outbound

This paper cites Fourier Neural Operator for Image Classification.

A neural operator view on U-Nets for inverse imaging problems Fourier Neural Operator for Image Classification

Reference 32

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This paper cites Resolution-Invariant Image Classification Based on Fourier Neural Operators.

A neural operator view on U-Nets for inverse imaging problems Resolution-Invariant Image Classification Based on Fourier Neural Operators

Reference 33

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Observation d289f64b-96aa-4d26-9d6d-af98b76cb54f · outbound

This paper cites Super-Resolution Neural Operator.

A neural operator view on U-Nets for inverse imaging problems Super-Resolution Neural Operator

Reference 34

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Observation 515860d8-3205-4f01-a260-c4dc5695f90a · outbound

This paper cites On Universal Approxima- tion and Error Bounds for Fourier Neural Operators.

A neural operator view on U-Nets for inverse imaging problems On Universal Approxima- tion and Error Bounds for Fourier Neural Operators

Reference 35

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Observation b685c2af-6d7c-4137-a818-8aca7f7916ce · outbound

This paper cites Convergence Rates for Learning Linear Operators from Noisy Data.

A neural operator view on U-Nets for inverse imaging problems Convergence Rates for Learning Linear Operators from Noisy Data

Reference 36

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Observation 212042fd-0e81-4bdf-97ab-7f6b0595a4b1 · outbound

This paper cites Reinhardt, S.

A neural operator view on U-Nets for inverse imaging problems Reinhardt, S

Reference 37

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Observation adf7cb38-8ba5-4965-96b0-fb7b0770de9b · outbound

This paper cites Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective.

A neural operator view on U-Nets for inverse imaging problems Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective

Reference 38

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This paper cites Multi-level monte carlo training of neural oper- ators.

A neural operator view on U-Nets for inverse imaging problems Multi-level monte carlo training of neural oper- ators

Reference 39

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This paper cites SERNet-Former: Segmentation by Efficient-ResNet with Attention-Boosting Gates and Attention-Fusion Networks.

A neural operator view on U-Nets for inverse imaging problems SERNet-Former: Segmentation by Efficient-ResNet with Attention-Boosting Gates and Attention-Fusion Networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.527977Z

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Observation 82f4a5ea-63e9-4fb1-a4c8-c315de09c544 · outbound

This paper cites Quarteroni, R.

A neural operator view on U-Nets for inverse imaging problems Quarteroni, R

Reference 41

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This paper cites Grafakos.Classical Fourier Analysis.

A neural operator view on U-Nets for inverse imaging problems Grafakos.Classical Fourier Analysis

Reference 42

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Observation 1c1d570a-86d3-49c7-bcb2-b441144073ef · outbound

This paper cites Spectral Neural Operators.

A neural operator view on U-Nets for inverse imaging problems Spectral Neural Operators

Reference 43

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Observation 889329e5-8e68-44d1-a69d-b0fb7806f507 · outbound

This paper cites Tr¨ oltzsch.Optimal Control of Partial Differential Equations.

A neural operator view on U-Nets for inverse imaging problems Tr¨ oltzsch.Optimal Control of Partial Differential Equations

Reference 44

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Observation 45770f6d-dd73-472f-8829-53ac41e4c932 · outbound

This paper cites Deep Parametric Continuous Convolutional Neural Net- works.

A neural operator view on U-Nets for inverse imaging problems Deep Parametric Continuous Convolutional Neural Net- works

Reference 45

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A neural operator view on U-Nets for inverse imaging problems Unresolved cited work

Reference 46

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A neural operator view on U-Nets for inverse imaging problems Unresolved cited work

Reference 47

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This paper cites Ambrosio, N.

A neural operator view on U-Nets for inverse imaging problems Ambrosio, N

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T22:38:14.895203Z

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A neural operator view on U-Nets for inverse imaging problems Unresolved cited work

Reference 49

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Observation c31fe22b-5644-4b58-b9e5-0db5657c341c · outbound

This paper cites Neural ordinary differential equations.

A neural operator view on U-Nets for inverse imaging problems Neural ordinary differential equations

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.469070Z

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Observation 5db5f469-d70f-41e1-b8b1-e4c33236c385 · outbound

This paper cites A Proposal on Machine Learning via Dynamical Systems.

A neural operator view on U-Nets for inverse imaging problems A Proposal on Machine Learning via Dynamical Systems

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.455184Z

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Observation 1d5fb15b-d78b-4d82-8b18-5c7b49717f13 · outbound

This paper cites Stable architectures for deep neural net- works.

A neural operator view on U-Nets for inverse imaging problems Stable architectures for deep neural net- works

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.440792Z

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Observation b8e8a974-bcc6-48b5-8050-4f10f0d65f7e · outbound

This paper cites Deep limits of residual neural net- works.

A neural operator view on U-Nets for inverse imaging problems Deep limits of residual neural net- works

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:38:16.425712Z

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