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Paper Citation Record · LEDGER

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions

As of 21 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.18219.

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pith.paper-citation-record.v1
2501.18219 v1

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measured 37 of 37 reference resolution

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37 of 37 outbound references displayed

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Outbound references

Observation 603094f3-9b7c-4ad9-8e5c-163ab935b7e0 · outbound

This paper cites Operator discretization library (ODL).

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Operator discretization library (ODL)

Reference 1

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This paper cites Compressed sensing for inverse problems and the sample complexity of the sparse Radon transform.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Compressed sensing for inverse problems and the sample complexity of the sparse Radon transform

Reference 2

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Observation 03daaec4-36ea-4b04-9ee0-c5b83ae52560 · outbound

This paper cites Deep microlocal reconstruc- tion for limited-angle tomography.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Deep microlocal reconstruc- tion for limited-angle tomography

Reference 3

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This paper cites Extraction of digital wavefront sets using applied harmonic analysis and deep neural networks.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Extraction of digital wavefront sets using applied harmonic analysis and deep neural networks

Reference 4

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This paper cites Model-based deep learning approaches to the Helsinki Tomography Challenge 2022.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Model-based deep learning approaches to the Helsinki Tomography Challenge 2022

Reference 5

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This paper cites Solving inverse problems using data-driven models.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Solving inverse problems using data-driven models

Reference 6

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This paper cites Modern regularization methods for inverse problems.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Modern regularization methods for inverse problems

Reference 7

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Observation 91de588c-1d68-45d5-b92e-e5e6c1cf6bd7 · outbound

This paper cites Analyzing reconstruction artifacts from arbitrary incomplete X-ray CT data.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Analyzing reconstruction artifacts from arbitrary incomplete X-ray CT data

Reference 8

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This paper cites Deep neural networks for inverse problems with pseudodifferential operators: An application to limited-angle tomography.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Deep neural networks for inverse problems with pseudodifferential operators: An application to limited-angle tomography

Reference 9

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This paper cites Learning the invisible: A hybrid deep learning-shearlet framework for limited angle computed tomography.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Learning the invisible: A hybrid deep learning-shearlet framework for limited angle computed tomography

Reference 10

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This paper cites Data-driven models in inverse problems.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Data-driven models in inverse problems

Reference 11

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This paper cites Continuous curvelet transform: I.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Continuous curvelet transform: I

Reference 12

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions An iterative thresholding algorithm for linear inverse problems with a sparsity constraint

Reference 13

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This paper cites The ill-conditioned nature of the limited angle tomography problem.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions The ill-conditioned nature of the limited angle tomography problem

Reference 14

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This paper cites Injectivity and weak*-to-weak continuity suffice for convergence rates in ℓ1-regularization.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Injectivity and weak*-to-weak continuity suffice for convergence rates in ℓ1-regularization

Reference 15

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Sparse regularization in limited angle tomography

Reference 16

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This paper cites Characterization and reduction of artifacts in limited angle tomogra- phy.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Characterization and reduction of artifacts in limited angle tomogra- phy

Reference 17

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Sparse regularization with ℓq penalty term

Reference 18

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Necessary and sufficient conditions for linear convergence of ℓ1-regularization

Reference 19

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Non-local inversion formulas for the X-ray transform

Reference 20

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Estimates for singular Radon transforms and pseudodifferential operators with singular symbols

Reference 21

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This paper cites Tomosipo: fast, flexible, and convenient 3D tomography for complex scanning geometries in Python.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Tomosipo: fast, flexible, and convenient 3D tomography for complex scanning geometries in Python

Reference 22

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Wavelets: an analysis tool

Reference 23

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions The analysis of linear partial differential operators, vols

Reference 24

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Local tomography for the limited-angle problem

Reference 25

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Benchmarking learned algorithms for computed tomography image reconstruction tasks

Reference 26

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Microlocal Analysis in Tomography

Reference 27

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Resolution of the wavefront set using continuous shearlets

Reference 28

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions PyWavelets: A Python package for wavelet analysis

Reference 29

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions A wavelet tour of signal processing, 1999

Reference 30

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This paper cites How strong are streak artifacts in limited angle computed tomography? Inverse Problems, 31(5):055003, 2015.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions How strong are streak artifacts in limited angle computed tomography? Inverse Problems, 31(5):055003, 2015

Reference 31

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Singularities of the X-ray transform and limited data tomography in R2 and R3

Reference 32

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Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Artifacts and visible singularities in limited data X-ray tomography

Reference 33

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Observation 33191a38-eda1-4c06-8df8-bba25c69d259 · outbound

This paper cites Learning a microlocal prior for limited-angle tomography.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Learning a microlocal prior for limited-angle tomography

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:21:37.316626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:21:37.212996Z digest=sha256:cc0e82c20bedca420f836e8edf3a684a12f87b5f916d96574354b505f5c82ef3

Observation 89aea8ef-8b21-4c04-8923-855348980020 · outbound

This paper cites Applications of microlocal analysis in inverse problems.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Applications of microlocal analysis in inverse problems

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:21:37.304039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:21:37.217069Z digest=sha256:347958c905cc6c86f358b8fe92c7850d78379ad8f2767a0b7ba9c95993b9a3ce

Observation a0a023da-7c8c-41c8-ba1e-ba61f08831d6 · outbound

This paper cites Sparse image and signal processing: wavelets, curvelets, morphological diversity.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Sparse image and signal processing: wavelets, curvelets, morphological diversity

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:21:37.291348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:21:37.221170Z digest=sha256:f9f45d1a9d3d1c10017ecd3e09c194db978acc0d3f951926243e21aedd6c59c7

Observation d20b8de4-f724-46da-b397-00b7951685c2 · outbound

This paper cites Robustness of data-driven approaches in limited angle tomography.

Revisiting $\Psi$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions Robustness of data-driven approaches in limited angle tomography

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-10T00:21:37.261945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T00:21:37.225400Z digest=sha256:11bff01a31aac88dc688001f1fc1e27d90c1103e5d9dbe053b1968468cee8d9e

Pith citing papers

No inbound Pith citation observations are available.