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Paper Citation Record · LEDGER

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging

As of 22 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2501.05583.

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pith.paper-citation-record.v1
2501.05583 v1

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measured 60 of 60 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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60 of 60 outbound references displayed

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Outbound references

Observation f4f070a0-98bd-4beb-b2d0-d094455c603e · outbound

This paper cites Tomographic imaging using the nonlinear response of magnetic particles.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Tomographic imaging using the nonlinear response of magnetic particles

Reference 1

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Observation 97942a3c-7070-4c76-bbd3-f6700f3a6bb6 · outbound

This paper cites Magnetic particle imaging: From proof of principle to preclinical applications.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Magnetic particle imaging: From proof of principle to preclinical applications

Reference 2

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Observation 1a40c246-5d65-4b8b-acac-ddb71cbb6681 · outbound

This paper cites Magnetic particle imaging: Introduction to imaging and hardware realization.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Magnetic particle imaging: Introduction to imaging and hardware realization

Reference 3

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Observation 6b13b147-6b0d-44b8-92c9-2fd82f7e8dcb · outbound

This paper cites Experimental results on fast 2D-encoded magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Experimental results on fast 2D-encoded magnetic particle imaging

Reference 4

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Observation fcc49bde-eb09-42f9-85fc-e3b8de7b7e09 · outbound

This paper cites Online reconstruction of 3D magnetic particle imaging data.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Online reconstruction of 3D magnetic particle imaging data

Reference 5

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Observation d1b7ffe6-9966-419a-9e8b-292271502d99 · outbound

This paper cites Magnetic particle imaging for quantification of vascular stenoses: A phantom study.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Magnetic particle imaging for quantification of vascular stenoses: A phantom study

Reference 6

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Observation 30534edf-a2d3-4f57-a69f-37e62018fc40 · outbound

This paper cites Three-dimensional real-time in vivo magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Three-dimensional real-time in vivo magnetic particle imaging

Reference 7

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Observation d1a3aaf2-8a44-4679-a92e-c9a63ee0b7ce · outbound

This paper cites Magnetic particle imaging for in vivo blood flow velocity measurements in mice.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Magnetic particle imaging for in vivo blood flow velocity measurements in mice

Reference 8

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Observation 49ace151-9112-4ead-99c5-26e570888bf4 · outbound

This paper cites Magnetic particle imaging: Visualization of instruments for cardiovascular intervention.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Magnetic particle imaging: Visualization of instruments for cardiovascular intervention

Reference 9

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Observation 521b514b-f4b3-44d8-95d6-1cb7a5bc28d7 · outbound

This paper cites Magnetic particle imaging–guided stenting.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Magnetic particle imaging–guided stenting

Reference 10

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Observation f03c59fe-3cc4-4cef-a533-a24f0fc4e5b4 · outbound

This paper cites Interactive magnetic catheter steering with 3-D real-time feedback using multi-color magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Interactive magnetic catheter steering with 3-D real-time feedback using multi-color magnetic particle imaging

Reference 11

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Observation 5586fd2b-ebf4-4000-a44c-0bd05cafdd4f · outbound

This paper cites First dedicated balloon catheter for magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging First dedicated balloon catheter for magnetic particle imaging

Reference 12

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Observation 76d1eb9f-50e0-42d9-9dec-6283c27b4b41 · outbound

This paper cites Quan- titative.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Quan- titative

Reference 13

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Observation 31729a08-e705-4abe-bd6c-4c2b850ac39b · outbound

This paper cites A perspective on cell tracking with magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging A perspective on cell tracking with magnetic particle imaging

Reference 14

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This paper cites In vivo cellular magnetic imaging: Labeled versus unlabeled cells.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging In vivo cellular magnetic imaging: Labeled versus unlabeled cells

Reference 15

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Observation 4ca2b8ba-00fa-438b-a00c-3f705966a1b4 · outbound

This paper cites Magnetic particle imaging: A novel in vivo imaging platform for cancer detection.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Magnetic particle imaging: A novel in vivo imaging platform for cancer detection

Reference 16

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Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging High-performance iron oxide nanoparticles for magnetic particle imaging–guided hyperthermia (hMPI)

Reference 17

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Observation 0f1ad635-9a57-47c5-8b39-2ce7be602b62 · outbound

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Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Weighted iterative reconstruction for magnetic particle imaging

Reference 18

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Observation 35de4c02-d50a-48e6-903f-af97c8fb34e7 · outbound

This paper cites Singular value analysis for magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Singular value analysis for magnetic particle imaging

Reference 19

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Observation ca8712f9-9c1e-4751-a227-95c8c700033d · outbound

This paper cites Model- based reconstruction for magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Model- based reconstruction for magnetic particle imaging

Reference 20

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This paper cites 2D model-based reconstruction for magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging 2D model-based reconstruction for magnetic particle imaging

Reference 21

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Observation 9a73d2c0-23c8-4c47-a982-54876d66c4a9 · outbound

This paper cites Nonlinear behavior of magnetic fluid in Brownian relaxation: Numerical simulation and derivation of empirical model.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Nonlinear behavior of magnetic fluid in Brownian relaxation: Numerical simulation and derivation of empirical model

Reference 22

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Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Mathematical models for magnetic particle imaging

Reference 23

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correction dated 2020-02-11. Source: crossref record 10.1088/1361-6420/ab5483->10.1088/1361-6420/aac535:correction, observed 2026-07-11T03:05:00.11129+00:00. This notice travels one citation hop only.

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This paper cites Towards accurate modeling of the multidimensional magnetic particle imaging physics.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Towards accurate modeling of the multidimensional magnetic particle imaging physics

Reference 24

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This paper cites Modeling the magnetization dynamics for largeensemblesofimmobilizedmagneticnanoparticlesinmulti-dimensionalmagneticparticleimaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Modeling the magnetization dynamics for largeensemblesofimmobilizedmagneticnanoparticlesinmulti-dimensionalmagneticparticleimaging

Reference 25

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This paper cites Equilibrium model with anisotropy for model-based reconstruction in magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Equilibrium model with anisotropy for model-based reconstruction in magnetic particle imaging

Reference 26

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This paper cites Sensitivity enhance- ment in magnetic particle imaging by background subtraction.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Sensitivity enhance- ment in magnetic particle imaging by background subtraction

Reference 27

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Observation 9d2de604-b3cd-460c-9f14-4efe096c78b8 · outbound

This paper cites Correction of linear system drifts in magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Correction of linear system drifts in magnetic particle imaging

Reference 28

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Observation db903bb3-7a83-4ea9-9bc6-43873aabb9a1 · outbound

This paper cites Enhanced reconstruction in magnetic particle imaging by whitening and random- ized SVD approximation.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Enhanced reconstruction in magnetic particle imaging by whitening and random- ized SVD approximation

Reference 29

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Observation 2adc26d8-1db5-40db-994e-ef453028c39c · outbound

This paper cites Model uncertainty in magnetic particle imaging: Nonlinear problem formulation and model-based sparse reconstruction.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Model uncertainty in magnetic particle imaging: Nonlinear problem formulation and model-based sparse reconstruction

Reference 30

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Observation b7af1bd4-7878-4a22-a5e1-77efd22c4b1e · outbound

This paper cites Inverse problems with inexact forward operator: Iterative regu- larization and application in dynamic imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Inverse problems with inexact forward operator: Iterative regu- larization and application in dynamic imaging

Reference 31

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Observation e995dd3e-4fdb-4a27-884e-67ba2df2625c · outbound

This paper cites Improved image reconstruction in magnetic particle imaging using structural a priori information.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Improved image reconstruction in magnetic particle imaging using structural a priori information

Reference 33

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Observation afdce368-4a19-40ec-86cd-2f93e1bab125 · outbound

This paper cites Edge preserving and noise reducing reconstruction for magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Edge preserving and noise reducing reconstruction for magnetic particle imaging

Reference 34

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Observation f99287ca-7634-45d8-925b-5c105f38e451 · outbound

This paper cites L1 data fitting for robust reconstruction in magnetic particle imaging: Quantitative evalu- ation on Open MPI dataset.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging L1 data fitting for robust reconstruction in magnetic particle imaging: Quantitative evalu- ation on Open MPI dataset

Reference 35

Resolution
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Observation b074870e-baf8-4f31-ba8e-f4407197866d · outbound

This paper cites A deep learning approach for automatic image reconstruction in MPI.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging A deep learning approach for automatic image reconstruction in MPI

Reference 36

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 66f70744-c7bb-4954-ad6a-330bad34ac16 · outbound

This paper cites Data augmentation for training a neural network for image reconstruction in MPI.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Data augmentation for training a neural network for image reconstruction in MPI

Reference 37

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:18:50.304724Z digest=sha256:4d600b6cc737b6f87794cf5ccf7a7ec46c9614b3744b0b666a6948aabe6cbaa1

Observation a6fc96ca-49a1-4c57-932a-dc7973053dcc · outbound

This paper cites Reconstruction of 1D images with a neural network for magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Reconstruction of 1D images with a neural network for magnetic particle imaging

Reference 38

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 3f2ba12f-f38c-4b7f-8f26-abe2b583ae4d · outbound

This paper cites Neural network for reconstruction of MPI images.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Neural network for reconstruction of MPI images

Reference 39

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2ccfa61b-46f2-4431-8ac2-90fc4ab679cf · outbound

This paper cites PP-MPI: A deep plug- and-play prior for magnetic particle imaging reconstruction.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging PP-MPI: A deep plug- and-play prior for magnetic particle imaging reconstruction

Reference 40

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d7984a51-3a51-46d9-8084-57d828facc6f · outbound

This paper cites A denoiser scaling technique for plug-and-play MPI reconstruction.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging A denoiser scaling technique for plug-and-play MPI reconstruction

Reference 41

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 1ccbbdc1-1deb-4b3b-b03e-aea99f5d37bd · outbound

This paper cites DEQ-MPI: A deep equilibrium reconstruction with learned consistency for magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging DEQ-MPI: A deep equilibrium reconstruction with learned consistency for magnetic particle imaging

Reference 43

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 34af4bcd-252b-419d-b005-af9f2805df37 · outbound

This paper cites A deep equilibrium technique for 3D MPI reconstruction.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging A deep equilibrium technique for 3D MPI reconstruction

Reference 44

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation b4abd90a-d03b-4860-985e-8f01135fb722 · outbound

This paper cites Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset

Reference 45

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metadata mismatch
raw_fallback, observed 2026-08-10T21:18:51.195558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 003efc0f-1aec-47a7-a790-d1b3e19de0b7 · outbound

This paper cites OpenMPIData: An initiative for freely accessible magnetic particle imaging data.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging OpenMPIData: An initiative for freely accessible magnetic particle imaging data

Reference 46

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:18:50.361980Z digest=sha256:0151f16729ab1c8147fb11c329e280484d16f4f836d7d924450fd297b2485bd9

Observation 268ba5fe-85bb-4ce9-97f7-44e900235a5d · outbound

This paper cites Deep learning for improving the spatial resolution of magnetic particle imaging.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Deep learning for improving the spatial resolution of magnetic particle imaging

Reference 47

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e07f2c16-64cc-461b-b5f0-5a56fa97b555 · outbound

This paper cites Shared prior learning of energy-based models for image reconstruction.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Shared prior learning of energy-based models for image reconstruction

Reference 48

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f853cacf-acb8-4e3f-b896-537f74470019 · outbound

This paper cites 8. Bilevel approaches for learning of variational imaging models.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging 8. Bilevel approaches for learning of variational imaging models

Reference 49

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 364d357c-402d-41b3-b1ad-748e9461dd52 · outbound

This paper cites The MNIST database of handwritten digits.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging The MNIST database of handwritten digits

Reference 50

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 80712a4b-5a25-44cb-9e5d-1501c6671d9c · outbound

This paper cites On row relaxation methods for large constrained least squares problems.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging On row relaxation methods for large constrained least squares problems

Reference 51

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5c8e6583-86be-492d-bdc0-79f7bd797e1d · outbound

This paper cites an unresolved cited work.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Unresolved cited work

Reference 52

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metadata mismatch
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d3955c79-4b73-4e7c-b5ac-798af8ab00ec · outbound

This paper cites Experimental parameter calibration of the scanner model for model-based MPI.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Experimental parameter calibration of the scanner model for model-based MPI

Reference 53

Resolution
metadata mismatch
raw_fallback, observed 2026-08-10T21:18:51.291486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a293d9e0-dce0-4949-9c4c-1db9b7ef9e94 · outbound

This paper cites Statistical and Computational Inverse Problems.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Statistical and Computational Inverse Problems

Reference 54

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f5db8466-f0e4-4190-a934-118df8c214d3 · outbound

This paper cites MDF: Magnetic Particle Imaging Data Format.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging MDF: Magnetic Particle Imaging Data Format

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-10T21:18:50.496765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 6957301b-7b21-47ea-820e-a66be5af6890 · outbound

This paper cites Solving the MPI reconstruction problem with automatically tuned regularization parameters.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Solving the MPI reconstruction problem with automatically tuned regularization parameters

Reference 56

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c8f2cdcb-99cf-47b0-92c9-b28579c46b18 · outbound

This paper cites Image quality assessment: From error visibility to structural similarity.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Image quality assessment: From error visibility to structural similarity

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T21:18:50.418812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:18:50.418812Z digest=sha256:e166999408c7a97f522f82ba0aa837a348a339efa0cd904a8fc21b88ee197a21

Observation 7a52119c-5dbc-46f8-8a64-2b0c2ef24d72 · outbound

This paper cites Glow: Generative flow with invertible 1x1 convolutions.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Glow: Generative flow with invertible 1x1 convolutions

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:18:52.787061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-10T21:18:50.424269Z digest=sha256:840d64c737d5a4b8d25ca773bc7910404f15524af5ecaa5488926dd131179bb3

Observation 29a3b4ae-4ab7-44d4-b1f1-2f1dca5e480c · outbound

This paper cites Density estimation using Real NVP.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Density estimation using Real NVP

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:18:52.766318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 1e92c08e-5213-42a6-b635-cebb30257fb4 · outbound

This paper cites an unresolved cited work.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Unresolved cited work

Reference 491

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verified exact
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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 27aea81a-9738-489e-ac0b-55154ef56c39 · outbound

This paper cites by Klaus Maier-Hein, Thomas M.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging by Klaus Maier-Hein, Thomas M

Reference 2022

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:18:50.315108Z digest=sha256:3881b06119ea89012eeb11703bf9e9efb367d4275a57b3410ca7ce584c0dc18b

Observation 2f11ea65-6dd6-49bb-b783-79d843dacbc8 · outbound

This paper cites an unresolved cited work.

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging Unresolved cited work

Reference 2023

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metadata mismatch
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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.